Patent Publication Number: US-2021165412-A1

Title: Control device, control method, and program

Description:
TECHNICAL FIELD 
     The present technology relates to a control device, a control method, and a program, and particularly to a control device, a control method, and a program that enable the action of a movable body to be planned in accordance with the value of a peripheral object. 
     BACKGROUND ART 
     With advances of, for example, artificial intelligence (AI), robots that act autonomously in accordance with the peripheral environment are becoming widespread. 
     Patent Document 1 discloses a technique of planning a movement route of a robot in order to minimize damage when peripheral objects collide with each other. The movement route of the robot is planned in order to minimize, for example, damage and adhesion of odors due to collision between objects. 
     Patent Document 2 discloses a technique of planning an action in order to avoid the periphery of an object of which position and posture are uncertain. For example, a grid map in which a weight corresponding to the uncertainty of the position and posture is set is generated to formulate a route. 
     CITATION LIST 
     Patent Document 
     
         
         Patent Document 1: International Publication No. 2010/004744 
         Patent Document 2: Japanese Patent Application Laid-Open No. 2005-032196 
       
    
     SUMMARY OF THE INVENTION 
     Problems to be Solved by the Invention 
     Various objects are present in the environment in which a robot acts, and their values are not the same. For objects valuable to the user, operations like careful handling including keeping away from the objects, holding the objects in a highly safe approach, and the like are required. 
     The present technology has been made in consideration of such a situation, and an object of the present technology is to enable planning the action of a movable body in accordance with the respective values of peripheral objects. 
     Solutions to Problems 
     The control device on one aspect of the present technology includes a value estimation unit configured to estimate a value of an object at a periphery of a movable body on the basis of sensor data detected by the movable body, and an action planning unit configured to plan an action of the movable body on the basis of the value of the object estimated. 
     In one aspect of the present technology, a value of an object at a periphery of a movable body is estimated on the basis of sensor data detected by the movable body, and an action of the movable body is planned on the basis of the value of the object estimated. 
     Effects of the Invention 
     According to the present technology, the action of a movable body can be planned in accordance with the value of each peripheral object. 
     Note that the effects described herein are not necessarily limited, and thus any of the effects described in the present disclosure may be applicable. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  illustrates an exemplary environment in which a robot acts according to an embodiment of the present technology. 
         FIG. 2  is a block diagram illustrating an exemplary hardware configuration of the robot. 
         FIG. 3  is a block diagram illustrating an exemplary functional configuration of a control unit. 
         FIG. 4  is a block diagram illustrating an exemplary configuration of an object-price estimation unit. 
         FIG. 5  illustrates exemplary estimation of areas each including an object captured. 
         FIG. 6  is a block diagram illustrating an exemplary configuration of a price estimation unit. 
         FIG. 7  illustrates an exemplary calculation of local feature amounts. 
         FIG. 8  is a block diagram illustrating another exemplary configuration of the price estimation unit. 
         FIG. 9  is a block diagram illustrating an exemplary configuration of an action planning unit. 
         FIG. 10  illustrates an exemplary price map. 
         FIG. 11  illustrates an exemplary movement route plan. 
         FIG. 12  is a flowchart for explaining processing by a robot that plans a movement route. 
         FIG. 13  illustrates an exemplary external appearance of a robot. 
         FIG. 14  illustrates exemplary postures during movement. 
         FIG. 15  is a block diagram illustrating an exemplary configuration of an action planning unit that plans a state during movement. 
         FIG. 16  illustrates an exemplary price map. 
         FIG. 17  is a flowchart for explaining process by a robot that plans a posture during movement. 
         FIG. 18  illustrates an exemplary movement mode of the robot. 
         FIG. 19  illustrates an exemplary external appearance of a robot having object-holding mechanisms. 
         FIG. 20  illustrates an exemplary object-holding mode. 
         FIG. 21  is a block diagram illustrating an exemplary configuration of an action planning unit that plans a holding manner. 
         FIG. 22  illustrates an exemplary object to be held. 
         FIG. 23  is a flowchart for explaining processing by a robot that plans the holding mode. 
         FIG. 24  illustrates another exemplary external appearance of a robot having object-holding mechanisms. 
         FIG. 25  illustrates an exemplary measurement of flatness. 
         FIG. 26  illustrates an exemplary measurement result of the flatness. 
         FIG. 27  illustrates an exemplary configuration of a control system. 
         FIG. 28  is a block diagram of an exemplary configuration of a computer. 
     
    
    
     MODE FOR CARRYING OUT THE INVENTION 
     Hereinafter, embodiments for carrying out the present technology will be described. The description will be given in the following order. 
     1. Action Plan based on Value of Object 
     2. Exemplary Configuration of Robot 
     3. Movement Route Plan 
     4. Plan regarding State during Movement 
     5. Plan of Holding Manner 
     6. Modifications 
     &lt;Action Plan Based on Value of Object&gt; 
       FIG. 1  illustrates an exemplary environment in which a robot acts according to an embodiment of the present technology. 
     In the example of  FIG. 1 , a robot  1  is present in a room such as a living room. The robot  1  is a dog-shaped robot capable of quadrupedal walking. 
     The robot  1  executes a predetermined program with a built-in computer, and autonomously takes various types of actions including movement in accordance with a peripheral situation and the like. The robot  1  is a movable body capable of moving autonomously. 
     In this example, the robot capable of quadrupedal walking is regarded as a movable body. However, instead of the robot  1 , there may be used any of various types of movable bodies capable of moving autonomously such as a robot capable of bipedal walking and a so-called drone that is an aircraft capable of unmanned flight. 
     Various objects are present in the room where the robot  1  acts. In the example of  FIG. 1 , a vase O 1  and a chair O 2  are placed on the floor at the periphery of the robot  1 . 
     Various types of actions taken by the robot  1  are controlled in accordance with a plan generated by the robot  1  itself. In the robot  1 , the value of each object captured in an image shot by a camera mounted on the robot  1  is estimated, and future actions are sequentially planned on the basis of the estimated value of the object. 
     For example, in a case where the destination is over the vase O 1  and chair O 2  and the vase O 1  is more expensive than the chair O 2 , a route passing near the chair O 2  and passing a position as far away as possible from the vase O 1  is planned as a movement route. 
     After planning the movement route, the robot  1  will move to the destination so as to pass near the chair O 2  and pass the position as far away as possible from the vase O 1 . 
     In such a manner, a movement route of the robot  1  is planned in consideration of the respective values of objects such as the price. 
     Autonomous action of the robot  1  may result in hitting of part of the body of the robot  1  against a peripheral object. Planning, as a movement route, a route passing a position as far away as possible from an expensive object enables reducing the possibility of hitting against and damaging such an expensive object. 
     Various types of action plans other than the movement route plan are also similarly set in consideration of the value of the object. As described later, a plan of a state during movement in the case of moving to the destination and a plan of a holding manner in the case of holding an object are set in consideration of the values of the objects. 
     In the following, there will be mainly described that the value of each object will be evaluated on the basis of the price of the object; however, an indicator for determining the value of the object is not limited to the price. 
     For example, the value of each object may be determined with the manufacturing time of the object, the owner of the object, the design of the object, the size of the object, and the color of the object as indicators. 
     In a case where the manufacturing time of an object is used as an indicator, for example, a new object is evaluated as having a higher value, and an old object is evaluated as having a lower value than the new object. 
     In addition, in a case where the owner of an object is used as an indicator, an object of which owner is an adult is evaluated as having a higher value, and an object of which owner is a child is evaluated as having a lower value than the object of which owner is the adult. 
     The user himself/herself may be allowed to set the value of each object in the environment in which the robot  1  acts. Even in the case of an object having a low value on the basis of an objective indicator, for example the price, such an object may have a high value depending on the subjectivity of the user. Allowing the user himself/herself to set the value of each object makes it possible for the robot  1  to handle carefully various types of objects valuable to the user. 
     &lt;Exemplary Configuration of Robot&gt; 
       FIG. 2  is a block diagram illustrating an exemplary hardware configuration of the robot  1 . 
     As illustrated in  FIG. 2 , the robot  1  includes a control unit  31 , an input-output unit  32 , a drive unit  33 , a wireless communication unit  34 , and a power source unit  35 . The input-output unit  32 , the drive unit  33 , the wireless communication unit  34 , and the power source unit  35  are connected to the control unit  31 . 
     The control unit  31  includes a computer having a central processing unit (CPU), a read only memory (ROM), a random access memory (RAM), a flash memory, and the like. The CPU of the control unit  31  executes a predetermined program and controls the overall operation of the robot  1 . The computer included in the control unit  31  functions as a control device that controls the operation of the robot  1 . 
     For example, the control unit  31  recognizes peripheral objects on the basis of a shot image supplied from a camera  41  of the input-output unit  32 , and estimates the price of the object. The control unit  31  plans an action on the basis of the estimated price of the object, and controls each constituent of the drive unit  33  such that the action according to the plan is taken. 
     The input-output unit  32  includes the camera  41 , a microphone  42 , a speaker  43 , a touch sensor  44 , and a light emitting diode (LED)  45 . 
     The camera  41  corresponds to each eye of the robot  1  and sequentially shoots the peripheral environment. The camera  41  outputs, to the control unit  31 , data of the shot image that is a still image or a moving image obtained by shooting. 
     The microphone  42  corresponds to each ear of the robot  1  and detects environmental sound. The microphone  42  outputs data of the environmental sound to the control unit  31 . 
     The speaker  43  corresponds to the mouth of the robot  1  and outputs a predetermined sound such as a spoken voice, an effect sound, and background music (BGM). 
     The touch sensor  44  is provided at a predetermined part such as the head or the back. The touch sensor  44  detects contact by the user, and outputs information representing the details of the contact by the user to the control unit  31 . 
     The LED  45  is provided at each part of the robot  1 , for example, at the position of each eye. The LED  45  emits light in accordance with control by the control unit  31  and presents information to the user. Instead of the LED  45 , a small display such as a liquid crystal display (LCD) or an organic electroluminescent (EL) display may be provided. Various types of images of each eye may be displayed on a display provided at the position of the eye, so that various types of facial expressions may be expressed. 
     The input-output unit  32  is provided with various types of modules such as a range sensor that measures a distance to each peripheral object and a positioning sensor such as a global positioning system (GPS). 
     The drive unit  33  drives in accordance with control by the control unit  31  and achieves an action of the robot  1 . The drive unit  33  includes a plurality of drive units provided for each joint shaft for roll, pitch, yaw, or the like. 
     The drive units are provided one-to-one, for example, at the joints of the robot  1 . The drive units each include the combination of a motor that rotates axially, an encoder that detects the rotational position of the motor, and a driver that adaptively controls the rotational position and rotational speed of the motor on the basis of the output of the encoder. The hardware configuration of Robot  1  is determined by, for example, the number of drive units and the positions of the drive units. 
     In the example of  FIG. 2 , drive units  51 - 1  to  51 - n  are provided. For example, the drive unit  51 - 1  includes a motor  61 - 1 , an encoder  62 - 1 , and a driver  63 - 1 . The drive units  51 - 2  to  51 - n  each also has a configuration similar to that of the drive unit  51 - 1 . 
     The wireless communication unit  34  is a wireless communication module such as a wireless local area network (LAN) module and a mobile communication module compatible with long term evolution (LTE). The wireless communication unit  34  communicates with a device connected to an indoor network or an external device such as a server on the Internet. The wireless communication unit  34  transmits data supplied from the control unit  31  to the external device, and receives data transmitted from the external device. 
     The power source unit  35  supplies power to each constituent in the robot  1 . The power source unit  35  includes a rechargeable battery  71  and a charging-discharging control unit  72  that manages the charging-discharging state of the rechargeable battery  71 . 
       FIG. 3  is a block diagram illustrating an exemplary functional configuration of the control unit  31 . 
     As illustrated in  FIG. 3 , the control unit  31  includes a scene-image acquisition unit  101 , an object-price estimation unit  102 , an action planning unit  103 , and a drive control unit  104 . At least part of the functional units illustrated in  FIG. 3  is achieved by execution of the predetermined program by the CPU included in the control unit  31 . 
     The scene-image acquisition unit  101  acquires a shot image shot by the camera  41  as a scene image representing a peripheral situation (scene). The scene-image acquisition unit  101  acquires such a scene image repeatedly at a predetermined cycle. The scene image acquired by the scene-image acquisition unit  101  is supplied to the object-price estimation unit  102  and the action planning unit  103 . 
     The object-price estimation unit  102  analyzes the scene image and estimates an area including an object captured. The object-price estimation unit  102  extracts the estimated area from the entire scene image and generates a small image, and estimates the price of the object captured in the small image. The object-price estimation unit  102  outputs information regarding the estimated price to the action planning unit  103 . In such a manner, the object-price estimation unit  102  functions as a value estimation unit that estimates the price as the value of the object. 
     On the basis of the scene image supplied from the scene-image acquisition unit  101  and the estimated price represented by the information supplied from the object-price estimation unit  102 , the action planning unit  103  plans various types of actions such as a movement route plan, a plan of a state during moving, and a plan of a manner of holding an object. The action planning unit  103  outputs information regarding such a planned action to the drive control unit  104 . 
     The drive control unit  104  controls each drive unit of the drive unit  33  in accordance with the plan represented by the information supplied from the action planning unit  103 , and achieves the action of the robot  1 . 
       FIG. 4  is a block diagram illustrating an exemplary configuration of the object-price estimation unit  102 . 
     As illustrated in  FIG. 4 , the object-price estimation unit  102  includes an object-area estimation unit  111  and a price estimation unit  112 . 
     The object-area estimation unit  111  analyzes the scene image supplied from the scene-image acquisition unit  101  and groups pixels similar in colors and luminance. The object-area estimation unit  111  estimates, for example, a rectangular area surrounding a group of similar pixels as an area including an object captured. The object-area estimation unit  111  extracts the rectangular area estimated as the area including the object captured, from the scene image and generates a small image including the object captured. 
       FIG. 5  illustrates exemplary estimation of areas each including an object captured. 
     In a case where the scene image illustrated at the left end of  FIG. 5  is input, a rectangular area including a vase O 1  captured and a rectangular area including a chair O 2  captured are set as illustrated ahead of an arrow #1. Each rectangular area is extracted from the scene image, and a small image p 1  including the vase O 1  captured and a small image p 2  including the chair O 2  captured are generated as illustrated ahead of an arrow #2. 
     In a case where an inferencer that uses such a scene image as an input and outputs a rectangular area surrounding an object is generated in advance by learning, the rectangular area may be set with such an inferencer. 
     Each small image generated by the object-area estimation unit  111  is supplied to the price estimation unit  112  of  FIG. 4 . 
     The price estimation unit  112  estimates the price of the object captured in the small image supplied from the object-area estimation unit  111 , and outputs information regarding the estimated price. 
       FIG. 6  is a block diagram illustrating an exemplary configuration of the price estimation unit  112 . 
     As illustrated in  FIG. 6 , the price estimation unit  112  includes a local-feature-amount calculation unit  121 , a price search unit  122 , and a feature amount-price DB  123 . 
     The local-feature-amount calculation unit  121  analyzes the small image and calculates such a local-feature-amount vector including information regarding the local feature amount of each portion as illustrated in  FIG. 7 . In the example of  FIG. 7 , the local-feature amount of each portion of the vase O 1  captured in the small image p 1  is obtained. The local-feature-amount calculation unit  121  outputs the local-feature-amount vector to the price search unit  122 . 
     The price search unit  122  searches the feature amount-price DB  123  and acquires the price corresponding to the local-feature-amount vector supplied from the local-feature-amount calculation unit  121 . The feature amount-price DB  123  is a database (DB) including information in which the local-feature-amount vector is associated with the price. 
     The information of the feature amount-price DB  123  is updated by, for example, a system that estimates the price with the local-feature-amount vector as a query. As a system that extracts a local feature amount such as Histogram of Gradient (HoG) and estimates the price corresponding to the local feature amount with a classifiers such as k-neighbor search, Support Vector Machine, or Bug of Words, such a system is prepared in, for example, a predetermined server. 
     Communication is performed between the robot  1  and a server on the Internet at a predetermined timing, and the information of the feature amount-price DB  123  is updated on the basis of the information transmitted from the server. The system that updates the information of the feature amount-price DB  123  may be provided in the robot  1 , and the robot  1  itself may update the information of the feature amount-price DB  123 . 
       FIG. 8  is a block diagram illustrating another exemplary configuration of the price estimation unit  112 . 
     A price estimation unit  112  illustrated in  FIG. 8  includes a price-estimation neural network  131 . The price-estimation neural network  131  uses a small image as an input and outputs the estimated price of an object captured in the small image. 
     The price-estimation neural network  131  is an inferencer generated by learning such as so-called deep learning, in which a small image is used as learning data and a price is used as supervised data, for example. The price-estimation neural network  131  may be generated by unsupervised learning. Learning of the price-estimation neural network  131  may be performed in the robot  1  or may be performed by the server on the Internet. 
     &lt;Movement Route Plan&gt; 
     As an action plan of a robot  1 , an exemplary case of planning a movement route will be described. 
       FIG. 9  is a block diagram illustrating an exemplary configuration of the action planning unit  103 . 
     As illustrated in  FIG. 9 , the action planning unit  103  includes an obstacle detection unit  141  and a route planning unit  142 . The scene image output from the scene-image acquisition unit  101  is input to the obstacle detection unit  141 , and the information regarding the estimated price output from the object-price estimation unit  102  is input to the route planning unit  142 . 
     The obstacle detection unit  141  analyzes the scene image and detects a peripheral obstacle. Examples of the obstacle include wall faces of a room, furniture, and an object to be a price estimation target. The obstacle detection unit  141  outputs information representing the position, size, and the like of the obstacle to the route planning unit  142 . 
     The route planning unit  142  plans a movement route from the position of the robot  1  to the destination on the basis of the obstacle detected by the obstacle detection unit  141  and the price of each object estimated by the object-price estimation unit  102 . 
     The price of each object estimated by the object-price estimation unit  102  may be represented by such a price map as illustrated in  FIG. 10 . The price map is information generated by mapping the price to an area corresponding to the position of each object. 
     In the price map of  FIG. 10 , the shaded area is an area where an object having a price equal to or higher than a predetermined price is not placed. On the other hand, the vertically-long rectangular area on the left side indicated in light color is an area where an object having a price of 3000 yen is placed, and the vertically-long rectangular area on the right side indicated in dark color is an area where an object having a price of 3000000 yen is placed. 
     Such a price map is generated by the object-price estimation unit  102  and input to the route planning unit  142  as information regarding the estimated price. 
     Referring back to the description of  FIG. 9 , the movement route to the destination is planned, for example, by setting an initial route such as the shortest route for heading to the destination while avoiding an obstacle and modifying the initial route on the basis of the price of an object placed along the route. The modification of the initial route is performed such that a distance corresponding to the price of the object is ensured, for example. 
       FIG. 11  illustrates an exemplary movement route plan. 
     The ranges of the rectangular areas illustrated in A and B of  FIG. 11  each correspond to part of the room in which the robot  1  is present. The position of the vase O 1  placed in the room is represented by a diagonal triangle, and the position of the chair O 2  is represented by a diagonal circle. 
     A route #11 illustrated in A of  FIG. 11  is the initial route from the position P 1  of the robot  1  to the destination G. For example, the shortest route for heading to the destination while avoiding an obstacle without considering the value of each object is set as the route #11. 
     In order to move to the destination G, the robot  1  will pass between the vase O 1  and the chair O 2 . In a case where the value of each object is not considered, the initial route is set such that the robot  1  passes the position intermediate between the vase O 1  and the chair O 2 . 
     A route #12 illustrated in B of  FIG. 11  is a movement route to the destination G, which is planned in consideration of the value of each object. The route #11 is modified on the basis of the respective prices of the vase O 1  and the chair O 2 . As illustrated in B of  FIG. 11 , the route is planned such that the distance to the vase O 1  having a higher price is maximized and the robot  1  passes near the chair O 2 . 
     The movement route may be planned by weighting in accordance with the price of the vase O 1  and the price of the chair O 2 . For example, in a case where the price of vase O 1  is 10 times the price of chair O 2 , a movement route is planned such that the distance between the robot  1  and the vase O 1  (the coordinates of the robot  1  and the coordinates of an edge of the vase O 1 ) is always the distance 10 times the distance between the robot  1  and the chair O 2  (the coordinates of the robot  1  and the coordinates of an edge of the chair O 2 ). 
     The route planning unit  142  of  FIG. 9  outputs information regarding the movement route planned as above. The drive control unit  104  performs control such that the robot  1  moves in accordance with the movement route planned by the route planning unit  142 . 
     Here, the processing by the robot  1  that plans such a movement route will be described with reference to the flowchart of  FIG. 12 . 
     In step S 1 , the scene-image acquisition unit  101  acquires a scene image shot by the camera  41 . 
     In step S 2 , the object-area estimation unit  111  extracts each rectangular area including an object captured, from the scene image and generates a small image. 
     In step S 3 , the price estimation unit  112  estimates the price of each object captured in all the small images generated by the object-area estimation unit  111 . 
     In step S 4 , the price estimation unit  112  generates a price map on the basis of the estimated price of each object. 
     In step S 5 , the route planning unit  142  plans a movement route to the destination as described above on the basis of the price map, and ends the processing. The position of an obstacle detected by the obstacle detection unit  141  is also appropriately considered for the movement route plan. 
     With the above processing, the robot  1  can plan a route passing a position away from an expensive object, as a movement route. Furthermore, moving in accordance with such a movement route enables the robot  1  to reduce the possibility of damaging the expensive object. 
     &lt;Plan Regarding State During Movement&gt; 
     As an action plan of a robot  1 , an exemplary case of planning a state during movement will be described. 
       FIG. 13  illustrates an exemplary external appearance of the robot  1 . 
     In the example of  FIG. 13 , the robot  1  has a housing  11  having a horizontally-long rectangular shape with rounded corners in top view. The robot  1  is a movable body movable forward, backward, left, and right as indicated by arrows. The housing  11  has a bottom face (not illustrated) provided with mechanisms for movement such as wheels. 
     The robot  1  is capable of moving in a posture with the front face  11 A and the back face  11 B facing in the directions of movement as indicated by the arrows in the up-and-down direction. The robot  1  is also capable of moving in a posture with the left-side face  11 C and the right-side face  11 D facing in the directions of movement as indicated by the arrows in the left-and-right direction. 
     In the robot  1 , a posture during movement and a movement mode are planned on the basis of the price of peripheral objects. 
     •Plan of Posture During Movement 
     In a case where the robot  1  has the housing  11  described with reference to  FIG. 13 , the width of the housing  11  in the directions of movement differs depending on a posture during movement. The width of the housing  11  during movement in the posture with the front face  11 A and the back face  11 B facing the directions of movement is wider than the width of the housing  11  during movement in the posture with the left-side face  11 C and the right-side face  11 D facing the directions of movement. 
     As a plan of a posture during movement, the robot  1  moves in which posture is planned. 
       FIG. 14  illustrates exemplary postures during movement. 
     In the examples of A and B of  FIG. 14 , vertically-long rectangular shelves s 1  and s 2  are placed in parallel in plan view. It is assumed that various types of objects are disposed on the shelves s 1  and s 2  and the price of each object has been estimated. Furthermore, it is assumed that the movement route of the robot  1  is set as a route passing between the shelves s 1  and s 2 . 
     A of  FIG. 14  illustrates a posture in a case where the price of the objects disposed on the shelves s 1  and s 2  is lower than a predetermined price, and B of  FIG. 14  illustrates a posture in a case where the price of the objects is higher than the predetermined price. The price as a threshold for determining a posture is set in advance. 
     As illustrated in A of  FIG. 14 , in a case where the price of the objects is lower than the predetermined price, the posture with the front face  11 A and the back face  11 B facing in the directions of movement is planned as the posture during movement. 
     On the other hand, as illustrated in B of  FIG. 14 , in a case where the price of the objects is higher than the predetermined price, the posture with the left-side face  11 C and the right-side face  11 D facing in the directions of movement is planned as the posture during movement. 
     The posture in B of  FIG. 14  with the left-side face  11 C and the right-side face  11 D facing in the directions of movement is a posture in which the housing  11  has a narrower width in the left-and-right direction and thus enables maximizing the distance between the shelves s 1  and s 2 , in comparison with the posture in A of  FIG. 14  with the front face  11 A and the back face  11 B facing in the directions of movement. In other words, the former posture is less likely to hit the shelves s 1  and s 2  than the latter posture. 
     As described above, in the robot  1 , the posture during movement is switched on the basis of the price of the objects along the movement route. Planning and controlling the posture during movement as above enables reducing the possibility of damaging an expensive object. 
       FIG. 15  is a block diagram illustrating an exemplary configuration of an action planning unit  103  that plans the state during movement. 
     The configuration of the action planning unit  103  illustrated in  FIG. 15  is different from that of the action planning unit  103  illustrated in  FIG. 9  in that a state-during-movement planning unit  151  is provided instead of the route planning unit  142 . A scene image output from a scene-image acquisition unit  101  is input to an obstacle detection unit  141 , and information regarding an estimated price output from an object-price estimation unit  102  is input to the state-during-movement planning unit  151 . Description overlapping with that in  FIG. 9  will be omitted appropriately. 
     The state-during-movement planning unit  151  specifies the price of an object along a movement route on the basis of the information supplied from the object-price estimation unit  102 . The state-during-movement planning unit  151  plans such a movement route similarly to the route planning unit  142  of  FIG. 9 , and compares the price of the object along the movement route with a threshold price to determine the posture when passing between two objects. 
       FIG. 16  illustrates an exemplary price map including the positions where shelves s 1  and shelves s 2  are installed. 
     In the price map of  FIG. 16 , the areas of shelves s 1  and shelves s 2  are represented as light-colored areas. The total price of the objects disposed on the shelf s 1  is assumed to be 300000 yen higher than the threshold price. Similarly, the total price of the objects disposed on the shelf s 2  is also assumed to be 300000 yen higher than the threshold price. The estimated price of each object estimated by the object-price estimation unit  102  may be represented by such a price map as illustrated in  FIG. 16 . 
     Referring back to the description of  FIG. 15 , in the case of determining the posture for passing between the two objects, the state-during-movement planning unit  151  outputs information regarding the state during movement including the posture during movement. The information output from the state-during-movement planning unit  151  also includes information regarding the movement route. A drive control unit  104  performs control such that a robot  1  moves in the posture planned by the state-during-movement planning unit  151 . 
     Here, the processing by the robot  1  that plans such a posture during movement will be described with reference to the flowchart of  FIG. 17 . 
     The processing of steps S 51  to S 55  of  FIG. 17  is similar to that of steps S 1  to S 5  of  FIG. 12 . Overlapping description will be omitted appropriately. 
     That is, a small image is generated by extracting an area including an object captured, from a scene image, and the price of each object captured in the small image is estimated. A price map as described with reference to  FIG. 16  is generated on the basis of the estimated price, and a movement route is set on the basis of the price map. 
     In step S 56 , the state-during-movement planning unit  151  determines whether or not objects are present on both sides of the movable body and the price of the objects present on both sides thereof is higher than the threshold. 
     In a case where it is determined in step S 56  that the price of the objects on both sides of the movable body is lower than the threshold, in step S 57 , the state-during-movement planning unit  151  determines such that moving is performed in a normal posture. The normal posture referred to here is such a posture with the front face  11 A and the back face  11 B facing in the directions of movement as described with reference to A of  FIG. 14 . 
     On the other hand, in a case where it is determined in step S 56  that the price of the objects on both sides of the movable body is higher than the threshold, in step S 58 , the state-during-movement planning unit  151  determines such that moving is performed in a safe posture. The safe posture referred to here is such a posture with the left-side face  11 C and the right-side face  11 D facing in the directions of movement as described with reference to B of  FIG. 14 . 
     After the posture is determined in step S 57  or step S 58 , the processing ends. The posture during movement of the robot  1  is controlled in accordance with the plan including the posture determined as above. 
     •Plan of Movement Mode 
       FIG. 18  illustrates an exemplary movement mode of a robot  1 . 
     In the examples of A and B of  FIG. 18 , the robot  1  has a housing  11  provided with four arms of arms  12 - 1  to  12 - 4 . 
     For example, moving the portion connecting the arm  12 - 1  with the housing  11  and the portion connecting the arm  12 - 2  with the housing  11  allows the arm  12 - 1  and the arm  12 - 2  to extend one-to-one from the side faces of the housing  11 , or extend from the bottom face thereof. The arm  12 - 3  and the arm  12 - 4  are provided extending from the bottom face of the housing  11 . 
     A of  FIG. 18  illustrates a movement mode in a case where the price of objects is lower than a predetermined price, and B of  FIG. 18  illustrates a movement mode in a case where the price of the objects is higher than the predetermined price. The price as a threshold for determining a movement mode is set in advance. 
     As illustrated in A of  FIG. 18 , in a case where the price of peripheral objects is lower than the predetermined price, a mode of movement in bipedal walking with the arm  12 - 3  and arm  12 - 4  is planned as the movement mode. 
     In the example of A of  FIG. 18 , the arm  12 - 1  and the arm  12 - 2  extend one-to-one from the side faces of the housing  11 , and the two arms of the arm  12 - 3  and arm  12 - 4  are used as moving mechanisms. 
     On the other hand, as illustrated in B of  FIG. 18 , in a case where the price of the peripheral objects is higher than the predetermined price, a mode of movement in quadrupedal walking with the arms  12 - 1  to  12 - 4  is planned as the movement mode. 
     In the example of B of  FIG. 18 , the arm  12 - 1  and the arm  12 - 2  extend from the bottom face of the housing  11 , and the four arms of the arms  12 - 1  to  12 - 4  are used as moving mechanisms. 
     In such a manner, in the transformable robot  1 , the state-during-movement planning unit  151  switches, on the basis of the price of peripheral objects, the number of moving mechanisms to be used for movement and plans a movement mode. For example, although the bipedal-walking movement mode illustrated in A of  FIG. 18  is less stable than the quadrupedal-walking movement mode illustrated in B of  FIG. 18 , the bipedal-walking movement mode enables movement at a higher speed. 
     In the case of moving near an object having a higher price, moving in the quadrupedal-walking movement mode is planned with priority given to its stability. Thus, this planning enables reducing the possibility of damaging the expensive object. 
     In addition, in the case of moving near an object having a lower price, moving in the bipedal-walking movement mode is planned with priority given to its speed. Thus, this planning enables moving more quickly. 
     There has been described the case where the arms are each used as a mechanism for movement and the movement mode is controlled by switching the number of arms. However, in a case where tires are each used as a moving mechanism, the movement mode may be controlled by switching the number of tires. For example, in the case of moving near an object having a lower price, a two-wheel movement mode is selected, and in the case of moving near an object having a higher price, a four-wheel movement mode is selected. 
     The type itself of a mechanism to be used for movement may be switched such that in the case of moving near an object having a lower price, a movement mode with arms or tires is selected and such that in the case of moving near an object having a higher price, a movement mode of flying over the object is selected. 
     As a state during movement, a state different from the posture and the movement mode may be planned on the basis of the price of an object. 
     For example, it is possible that the moving speed of the robot  1  is planned on the basis of the price of peripheral objects, for example, such that the moving speed is set at a low speed in the case of passing near an object having a higher price and the moving speed is set at a high speed in the case of passing near an object having a lower price. 
     As above, automatic switching may be made between a mode with priority given to protection of an object and a mode with priority given to movement at the shortest distance or movement at the highest speed. Furthermore, the user may be able to select a mode to be prioritized. 
     &lt;Plan of Holding Manner&gt; 
     As an action plan of a robot  1 , an exemplary case of planning a manner of holding an object will be described. 
       FIG. 19  illustrates an exemplary external appearance of the robot  1  having object-holding mechanisms. 
     In the example of  FIG. 19 , the robot  1  has a housing  11  having a vertically-long rectangular shape with rounded corners in side view. The housing  11  has a front face  11 A provided with two arms  12 - 1  and  12 - 2  serving as object-holding mechanisms. Furthermore, the housing  11  has a bottom face  11 E provided with moving mechanisms such as wheels. 
     The robot  1  of  FIG. 19  is a movable body having a carrying function capable of holding an object or the like placed in a room by driving the arms  12 - 1  and  12 - 2  and carrying the object in that state to a predetermined position. 
     In such a robot  1 , a manner of holding an object such as a holding mode and a manner of placing an object being held is planned on the basis of the price of an object to be held. 
     •Plan of Holding Mode The object-holding mode includes a mode of holding one object with one arm and a mode of holding one object with two arms, for example. 
     As a plan of the holding mode, it is planned that a target object is to be held in which of the plurality of modes different in the number of mechanisms to be used for holding one object. 
       FIG. 20  illustrates an exemplary object-holding mode. 
     A of  FIG. 20  illustrates a holding mode in a case where the price of an object is lower than a predetermined price, and B of  FIG. 20  illustrates a holding mode in a case where the price of an object is higher than the predetermined price. The price as a threshold for determining a holding mode is set in advance. 
     As illustrated in A of  FIG. 20 , in a case where the price of an object is lower than the predetermined price, the mode of holding one object with one arm is planned as the holding mode. 
     In the example of A of  FIG. 20 , a glass O 31  is held with the arm  12 - 1 , and a dish O 32  is held with the arm  12 - 2 . Each of the glass O 31  and the dish O 32  is an object of which estimated price is lower than the price set as the threshold. 
     On the other hand, as illustrated in B of  FIG. 20 , in a case where the price of the object is higher than the predetermined price, the mode of holding one object with two arms is planned as the holding mode. 
     In the example of B of  FIG. 20 , a vessel O 41  is held with the arm  12 - 1  and the arm  12 - 2 . The vessel O 41  is an object of which estimated price is higher than the price set as the threshold. 
     As described above, in the robot  1 , a holding mode is planned by switching the number of mechanisms to be used for holding, on the basis of the price of an object to be held. 
     It is considered that the larger the number of mechanisms to be used for holding is, the safer an object can be held. Holding an expensive object with many mechanisms enables the robot  1  to reduce the possibility of damaging the expensive object. 
       FIG. 21  is a block diagram illustrating an exemplary configuration of an action planning unit  103  that plans a holding manner. 
     As illustrated in  FIG. 21 , the action planning unit  103  includes a holding-area estimation unit  161  and a holding planning unit  162 . A scene image output from a scene-image acquisition unit  101  is input to the holding-area estimation unit  161 , and information regarding an estimated price output from an object-price estimation unit  102  is input to the holding planning unit  162 . 
     The holding-area estimation unit  161  analyzes the scene image and detects a holding area including an object to be held captured. The holding-area estimation unit  161  outputs information representing the position, size, and the like of the object to be held to the holding planning unit  162 . 
     The holding planning unit  162  specifies the price of the object to be held, on the basis of the information supplied from the object-price estimation unit  102 . 
       FIG. 22  illustrates an exemplary object to be held. 
     In the example of  FIG. 22 , the area indicated by surrounding with the vertically-long rectangular frame has been detected by the holding-area estimation unit  161 , as a holding area including a vase O 1  that is an object to be held captured. In addition, it has been specified that the price of the vase O 1  is 3000000 yen on the basis of the information supplied from the object-price estimation unit  102 . 
     After specifying the price of the object to be held, the holding planning unit  162  plans a holding mode on the basis of the price of the object to be held. 
     The holding planning unit  162  outputs a holding plan including information regarding the holding manner, including information for designating the holding position of the object to be held by each arm, information for designating a movement route to the transport destination, and the like. A drive control unit  104  performs, for example, control such that arms  12 - 1  and  12 - 2  drive in accordance with the holding mode planned by the holding planning unit  162 . 
     Here, the processing by the robot  1  that plans such a holding mode will be described with reference to the flowchart of  FIG. 23 . 
     In step S 101 , the scene-image acquisition unit  101  acquires as a scene image shot by the camera  41 . 
     In step S 102 , the holding-area estimation unit  161  analyzes the scene image, determines an object to be held, and detects an area including the object to be held captured. 
     In step S 103 , on the basis of the price of each object estimated by the object-price estimation unit  102 , the holding planning unit  162  specifies the price of the object to be held. In the object-price estimation unit  102 , the price of each peripheral object is estimated and information regarding the estimated price is supplied to the holding planning unit  162 . 
     In step S 104 , the holding planning unit  162  determines whether or not the price of the object to be held is higher than the threshold. 
     In a case where it is determined in step S 104  that the price of the object to be held is lower than the threshold, in step S 105 , the holding planning unit  162  determines such that holding is performed with one arm. That is, as described with reference to A of  FIG. 20 , the mode of holding one object with one arm is planned as the holding mode. 
     On the other hand, in a case where it is determined in step S 104  that the price of the object to be held is higher than the threshold, in step S 106 , the holding planning unit  162  determines such that holding is performed with both arms. That is, as described with reference to B of  FIG. 20 , the mode of holding one object with two arms is planned as the holding mode. 
     After the number of mechanisms to be used for holding the object is determined in step S 105  or step S 106 , the processing ends. The holding manner of the robot  1  is controlled in accordance with the plan including the holding mode determined as above. 
     •Plan of Manner of Placing Object Being Held  FIG. 24  illustrates another exemplary external appearance of the robot  1  having object-holding mechanisms. 
     In the example of  FIG. 24 , a housing  11  has an upper face  11 F provided with a propeller  13  for causing a robot  1  to fly. That is, the robot  1  illustrated in  FIG. 24  is a drone capable of flying while holding an object. 
     Furthermore, a depth sensor  14  including a stereo camera, a time of flight (ToF) sensor, and the like is provided below the front face  11 A of the housing. The depth sensor  14  measures the height of each position of a placement face and calculates the flatness (horizontality). In the example of  FIG. 24 , the flatness of each position on the top plate of a table, which is the placement face for an object being held, is calculated. 
     In such a robot  1 , a placement position for the object being held is planned on the basis of the flatness of each position of the placement face and the price of the object being held. 
     For example, in a case where the price of the object being held is lower than a threshold price, it can be determined as the placement position for the object even if the flatness is lower than a threshold (position oblique to the horizontal plane). 
     On the other hand, in a case where the price of the object is higher than a predetermined price, it can be determined, of the entire top plate of the table, only the position where the flatness is higher than the threshold (position where part of the top plate close to the horizontal state), as the placement position for the object. 
     In such a manner, in the robot  1 , the placement position is planned by the holding planning unit  162  on the basis of the price of the object being held, and the operation of placing the object is controlled. 
     In a case where an object having a higher price is placed, a position having a higher flatness is set as the placement position, in comparison with a case where an object having a lower price is placed. Thus, this setting enables reducing the possibility of damaging the expensive object. Such a position having a higher flatness is less likely to slip off in comparison with an oblique position, and thus it can be said to be a safe position. 
       FIG. 25  illustrates an exemplary measurement of the flatness. 
     In  FIG. 25 , the arm  12 - 2  as one arm of the arms is used as a manipulator, and the leading end of the arm  12 - 2  comes into contact with the top plate such that the height of each position of the top plate is measured. 
     Moving the arm  12 - 2  as indicated by an arrow #21 with the leading end in contact with the top plate of the table results in obtaining such a measurement result as indicated in  FIG. 26 . The horizontal axis of  FIG. 26  represents the position on the top plate of the table, and the vertical axis represents the height from the ground surface. 
     In the robot  1 , for example, the difference between the height of a reference position and the heights of a plurality of positions around the reference position is calculated from such a measurement result as indicated in  FIG. 26 , and the flatness is calculated on the basis of the difference in height. In such a manner, various methods can be adopted as a manner of measuring the flatness. 
     Instead of the flatness, the level of unevenness, the level of slipperiness, the height, the color, and the like of the flat face may be measured, and the placement position may be planned. 
     For example, when considering the height for the placement position, for an object having a price higher than the threshold price, only the position lower than a threshold height can be determined as the placement position for the object being held. 
     In addition, when considering the color of a placement face for the placement position, for an object having a price higher than the threshold price, only the position in, for example, white or yellow where the object is distinctive when the object is placed can be determined as the placement position for the object. The placement position may also be determined in consideration of the color of an object itself being held. 
     For an object having a price lower than the threshold price, even an edge position of the table may be determined as the placement position, and for an object having a price higher than the threshold price, only the position near the center of the table can be determined as the placement position. 
     The speed of the placement operation by the robot  1  may be planned on the basis of the price of an object such that the speed of the placement operation is set at a slow speed, in the case of placing an object having a higher price, and such that the speed of the placement operation is set at a high speed in the case of placing an object having a lower price. 
     As above, in the robot  1 , an action is planned in order to keep away from an expensive object, move in a state where it is less likely to hit an expensive object, or hold an expensive object more safely. An expensive object will be handled carefully, as it is called. 
     &lt;Modifications&gt; 
     An action of a robot  1  may be planned by an external device on the basis of the price of objects at the periphery of the robot  1 . 
       FIG. 27  illustrates an exemplary configuration of a control system. 
     The control system of  FIG. 27  includes the robot  1 , a control server  201 , and a network  202  such as the Internet. The robot  1  and the control server  201  are connected via the network  202 . The robot  1  and the control server  201  communicate with each other via the network  202 . 
     In the control system of  FIG. 27 , an action of the robot  1  is planned by the control server  201  that is an external device of the robot  1 . Each functional unit of the control unit  31  of  FIG. 3  is achieved in the control server  201  by execution of a predetermined program. 
     A control unit  31  included in the control server  201  plans the action of the robot  1  in such a manner as described above on the basis of data transmitted from the robot  1 , and transmits information regarding the planned action to the robot  1 . Various types of data such as data of a shot image are repeatedly transmitted from the robot  1  to the control server  201 . 
     The robot  1  will take an action corresponding to the value of each peripheral object as described above in accordance with the plan represented by the information transmitted from the control server  201 . In such a manner, the control server  201  functions as a control device that plans and controls an action of the robot  1 . 
     In the above, the price of each object is estimated on the basis of a shot image shot by the camera of the robot  1 . The price of each object, however, may be estimated on the basis of sensor data different from the shot image. The value of each object can be estimated on the basis of various types of sensor data such as a distance to the object measured by a distance sensor and the temperature of the object measured by a temperature sensor. 
     •Exemplary Configuration of Computer The series of processing described above can be performed by hardware or software. In the case of performing the series of processing by the software, programs included in the software are installed from a program recording medium onto a computer embedded in dedicated hardware, a general-purpose personal computer, or the like. 
       FIG. 28  is a block diagram of an exemplary hardware configuration of a computer that performs the above series of processing in accordance with a program. The control server  201  of  FIG. 27  also has a configuration similar to that illustrated in  FIG. 28 . 
     A central processing unit (CPU)  1001 , a read only memory (ROM)  1002 , and a random access memory (RAM)  1003  are mutually connected via a bus  1004 . 
     Moreover, an input-output interface  1005  is connected to the bus  1004 . An input unit  1006  including a keyboard, a mouse, and the like and an output unit  1007  including a display, a speaker, and the like are connected to the input-output interface  1005 . Furthermore, a storage unit  1008  including a hard disk, a non-volatile memory, and the like; a communication unit  1009  including a network interface and the like; and a drive  1010  that drives a removable medium  1011  are connected to the input-output interface  1005 . 
     In the computer having the configuration as above, the CPU  1001  loads, for example, a program stored in the storage unit  1008 , into the RAM  1003  via the input-output interface  1005  and the bus  1004  to execute the program, so that the series of processing described above is performed. 
     The program executed by the CPU  1001  having recorded on the removable medium  1011  or the program executed by the CPU  1001  is provided via a wired or wireless transmission medium such as a local area network, the Internet, or a digital broadcast, and then installed in the storage unit  1008 , for example. 
     Note that the program executed by the computer may be a program for chronologically performing the processing in accordance with the order described in the present specification, may be a program for parallelly performing the processing or a program for performing the processing at a required timing, for example, when a call is made. 
     In the present specification, the system means a collection of a plurality of constituent elements (e.g., devices and modules (parts)), and thus it is not considered whether or not all the constituent elements are included in the same housing. Thus, a plurality of devices housed in separate housings and connected via a network, and one device having a plurality of modules housed in one housing are both systems. 
     Furthermore, the effects described in the present specification are merely exemplified and are not intended to be limiting, and there may be additional effects. 
     The embodiments of the present technology are not limited to the above embodiments, and thus various modifications can be made without departing from the gist of the present technology. 
     For example, the present technology can adopt a cloud computing configuration in which one function is shared and processed by a plurality of devices via a network. 
     Furthermore, each step described in the above flowcharts can be performed by one device, and can be shared and performed by a plurality of devices. 
     Moreover, in a case where a plurality of pieces of processing is included in one step, the plurality of pieces of processing included in the one step can be performed by one device, and can be performed by sharing among a plurality of devices. 
     •Examples of Configuration Combination 
     The present technology can also adopt the following configurations. 
     (1) 
     A control device including: 
     a value estimation unit configured to estimate a value of an object at a periphery of a movable body on the basis of sensor data detected by the movable body; and 
     an action planning unit configured to plan an action of the movable body on the basis of the value of the object estimated. 
     (2) 
     The control device according to (1), 
     in which the action planning unit plans a movement route to a destination. 
     (3) 
     The control device according to (2), 
     in which the action planning unit plans the movement route in which a distance corresponding to the value of the object is secured. 
     (4) 
     The control device according to (3), 
     in which in the case of passing between two pieces of the objects, the action planning unit plans the movement route passing closer to the object having a lower value than the object having a higher value. 
     (5) 
     The control device according to (2), further including: 
     an obstacle detection unit configured to detect an obstacle on the basis of the sensor data, 
     in which the action planning unit plans the movement route on the basis of the value of the object and a position of the obstacle. 
     (6) 
     The control device according to (1), 
     in which the action planning unit plans a posture of the movable body during movement of the movable body. 
     (7) 
     The control device according to (6), 
     in which the action planning unit plans, as the posture during the movement, an orientation of a housing of the movable body in a direction of the movement. 
     (8) 
     The control device according to (1), 
     in which the action planning unit plans a movement mode of the movable body. 
     (9) 
     The control device according to (8), 
     in which the action planning unit plans, as the movement mode, a mode different in a number of mechanisms to be used for movement. 
     (10) 
     The control device according to (1), 
     in which the movable body has a mechanism of holding the object, and 
     the action planning unit plans a holding mode for the object. 
     (11) 
     The control device according to (10), 
     in which the action planning unit plans, as the holding mode for the object, a mode different in a number of the mechanisms to be used for holding the object. 
     (12) 
     The control device according to (11), 
     in which in a case where the object having a higher value is held, the action planning unit plans a mode of using a number of the mechanisms larger than a number of the mechanisms to be used in a case where the object having a lower value is held. 
     (13) 
     The control device according to (1), 
     in which the movable body has a mechanism of holding the object, and 
     the action planning unit plans a manner of placing the object being held. 
     (14) 
     The control device according to (13), 
     in which the action planning unit plans, as the manner of placing the object, a placement position for the object. 
     (15) 
     The control device according to (14), 
     in which in a case where the object having a higher value is placed, the action planning unit plans, as the placement position, a position having a higher flatness, in comparison with a case where the object having a lower value is placed. 
     (16) 
     The control device according to any of (1) to (15), further including: 
     an acquisition unit configured to acquire, as the sensor data, a shot image that is an image shot by a camera provided at the movable body. 
     (17) 
     The control device according to (16), further including: 
     an area estimation unit configured to estimate an area including the object captured, from the shot image, 
     in which the value estimation unit analyzes the estimated area and estimates the value of the object. 
     (18) 
     A control method by a control device, including: 
     estimating a value of an object at a periphery of a movable body on the basis of sensor data detected by the movable body; and 
     planning an action of the movable body on the basis of the value of the object estimated. 
     (19) 
     A program for causing a computer to execute processing including: 
     estimating a value of an object at a periphery of a movable body on the basis of sensor data detected by the movable body; and 
     planning an action of the movable body on the basis of the value of the object estimated. 
     REFERENCE SIGNS LIST 
     
         
           1  Robot 
           31  Control unit 
           32  Input-output unit 
           33  Drive unit 
           34  Wireless communication unit 
           35  Power source unit 
           101  Scene-image acquisition unit 
           102  Object-price estimation unit 
           103  Action planning unit 
           104  Drive control unit 
           111  Object-area estimation unit 
           112  Price estimation unit 
           121  Local-feature-amount calculation unit 
           122  Price search unit 
           123  Feature amount-price DB 
           131  Price neural network 
           141  Obstacle detection unit 
           142  Route planning unit 
           151  State-during-movement planning unit 
           161  Holding-area estimation unit 
           162  Holding planning unit 
           201  Control server 
           202  Network