Patent Publication Number: US-2017357267-A1

Title: Autonomous work vehicle obstacle detection system

Description:
BACKGROUND 
     The invention relates generally to agricultural operations and, more specifically, to an obstacle detection system for an autonomous work vehicle. 
     Certain work vehicles, such as tractors or other prime movers, may be controlled by a control system (e.g., without operator input, with limited operator input, etc.) during certain phases of operation. For example, a controller may instruct a steering control system and/or a speed control system of the vehicle to automatically or semi-automatically guide the vehicle along a guidance swath within a field or other work area. However, the vehicle may encounter an obstacle during the operation. 
     BRIEF DESCRIPTION 
     In a first embodiment, a work vehicle includes at least one sensor configured to detect at least one property of a work area, and a controller comprising a processor operatively coupled to a memory, wherein the controller is configured to receive a first signal from an at least one sensor indicative of the at least one property of the work area, to determine whether an obstacle occupies one or more locations of the work area by creating or updating a map having one or more cells that correspond to the one or more locations of the work area, wherein each of the one or more cells indicate whether the obstacle occupies the respective locations of the work area based on the at least one property, and to send a second signal based on the map. 
     In a second embodiment, a work vehicle includes a lidar sensor, and a controller comprising a processor and a memory, wherein the controller is configured to receive a first signal from the lidar sensor indicating distances and directions to an obstacle in a work area, to create or update a point cloud having a set of points based on the distance and directions, to create or update a map of one or more cells that correspond to one or more locations of the work area, wherein each of the one or more cells indicate whether the obstacle occupies the respective locations of the work area based on the points of the point cloud, to send a second signal indicative of the map to a control system of the vehicle. 
     In a third embodiment, a control system for a work vehicle includes a controller comprising a processor and a memory, wherein the memory is operatively coupled to the processor, wherein the processor is configured to receive a first signal from a first sensor indicating distances and directions to an obstacle in the agricultural field, to create or update a map of one or more cells that correspond to one or more locations of the agricultural field, wherein each of the one or more cells indicate whether the obstacle occupies the respective locations of the agricultural field, and to send a second signal indicative of instructions to control the vehicle based on the map. 
    
    
     
       DRAWINGS 
       These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein: 
         FIG. 1  is a perspective view of an embodiment of a work vehicle that includes an obstacle detection system having one or more sensors; 
         FIG. 2  is a schematic diagram of an embodiment of the obstacle detection system that may be employed within the vehicle of  FIG. 1 ; 
         FIG. 3  is a flow diagram of an embodiment of a method performed by the obstacle detection system of  FIG. 1 ; 
         FIG. 4  is a flow diagram of an embodiment of a method performed by the obstacle detection system of  FIG. 1 ; 
         FIG. 5A  is a graph of an embodiment of data received by the obstacle detection system of  FIG. 2  having the sensors directed in a first direction; 
         FIG. 5B  is a graph of an embodiment of data received by the obstacle detection system of  FIG. 2  having the one or more sensors in a second direction. 
     
    
    
     DETAILED DESCRIPTION 
     Turning now to the drawings,  FIG. 1  is a perspective view of an embodiment of an autonomous work vehicle  10 , such as a tractor, that may include an obstacle detection system  12 . The autonomous vehicle  10  may include a control system configured to automatically guide the agricultural vehicle  10  through a work area, such as an agricultural field  14  (e.g., along a direction of travel  16 ) to facilitate operations (e.g., planting operations, seeding operations, application operations, tillage operations, harvesting operations, etc.). For example, the control system may automatically guide the vehicle  10  along a guidance path through the field  14  without input from an operator. 
     It should be noted that the techniques disclosed may be used on any desired type of vehicle, but are particularly useful for off-road and work vehicles. More particularly, one presently contemplated application is in the area of agricultural work operations, such as on farms, in fields, in operations entailed in preparing, cultivating, harvesting and working plants and fields, and so forth. While in the present disclosure reference may be made to the vehicle  10  as an “agricultural vehicle”, it should be borne in mind that this is only one particular area of applicability of the technology, and the disclosure should not be understood as limiting it to such applications. 
     To facilitate control of the autonomous agricultural vehicle  10 , the control system includes a spatial locating device, such as a Global Position System (GPS) receiver which is configured to output position information to a controller of the control system. The spatial locating device is configured to determine the position and/or orientation of the autonomous agricultural vehicle based on the spatial locating signals. The autonomous agricultural vehicle  10  may include one or more wheels  18  to facilitate movement of the autonomous agricultural vehicle  10 . Further, the autonomous agricultural vehicle  10  may be coupled to an agricultural implement to perform the agricultural operations. While the autonomous agricultural vehicle  10  is described in detail below, the autonomous agricultural vehicle may be any vehicle suitable for agricultural operations. 
     The obstacle detection system  12  may include one or more sensors to detect properties of the agricultural field  14  and to send signal(s) to a controller of the obstacle detection system  12 . The one or more sensors may be any sensors suitable to acquire data indicative of the properties of the agricultural field  14 . For example, the sensors may include one or more light detection and ranging (lidar) sensors, radio detection and ranging (radar) sensors, image sensors (e.g., RGB camera sensors, stereo camera sensors, etc.), infrared (IR) sensors, and the like. In the illustrated embodiment, the obstacle detection system  12  includes at least one lidar sensor  20  and at least one radar sensor  22 . The lidar sensor  20  and the radar sensor  22  may be coupled to the agricultural vehicle  10  in a front position  24 , in a top position  26 , or any suitable location to acquire data indicative of the properties of the agricultural field  14 . As described in detail below obstacle detection system  12  may include a controller that detects an obstacle  28  via data from the lidar sensor  20  and the radar sensor  22 . 
       FIG. 2  is a schematic diagram of an embodiment of the obstacle detection system  12  of a control system of the vehicle  10  of  FIG. 1 . The obstacle detection system  12  may include a spatial locating device  38  mounted to the autonomous agricultural vehicle  10  to determine a position, and in certain embodiments a velocity, of the autonomous agricultural vehicle  10 . The obstacle detection system  12  may include one or more spatial locating antennas  40  and  42  communicatively coupled to the spatial locating device  38 . Each spatial locating antenna is configured to receive spatial locating signals (e.g., GPS signals from GPS satellites) and to output corresponding spatial locating data to spatial locating device  38 . While the illustrated agricultural vehicle  10  includes two spatial locating antennas, it should be appreciated that in alternative embodiments, the control system may include more or fewer spatial locating antennas (e.g., 1, 2, 3, 4, 5, 6, or more). 
     In certain embodiments, the obstacle detection system  12  of the control system may also include an inertial measurement unit (IMU) communicatively coupled to the controller  44  and configured to enhance the accuracy of the determined position and/or orientation. For example, the IMU may include one or more accelerometers configured to output signal(s) indicative of acceleration along the longitudinal axis, the lateral axis, the vertical axis, or a combination thereof. In addition, the IMU may include one or more gyroscopes configured to output signal(s) indicative of rotation (e.g., rotational angle, rotational velocity, rotational acceleration, etc.) about the longitudinal axis, the lateral axis, the vertical axis, or a combination thereof. The controller may determine the position and/or orientation of the agricultural vehicle based on the IMU signal(s) while the spatial locating signals received by the spatial locating antennas are insufficient to facilitate position determination (e.g., while an obstruction, such as a tree or building, blocks the spatial locating signals from reaching the spatial locating antennas). In addition, the controller  44  may utilize the IMU signal(s) to enhance the accuracy of the determined position and/or orientation. For example, the controller  44  may combine the IMU signal(s) with the spatial locating data and/or the position determined by the spatial locating device (e.g., via Kalman filtering, least squares fitting, etc.) to determine a more accurate position and/or orientation of the agricultural vehicle (e.g., by compensating for movement of the spatial locating antennas resulting from pitch and/or roll of the agricultural vehicle as the agricultural vehicle traverses uneven terrain). 
     In certain embodiments, the IMU and the spatial locating device may be disposed within a common housing. In further embodiments, the IMU and one spatial locating antenna may be disposed within a common housing. For example, each spatial locating antenna housing may include a spatial locating antenna and an IMU. Furthermore, in certain embodiments, a portion of the spatial locating device and one spatial locating antenna may be disposed within a common housing. For example, a first portion of the spatial locating device and the first spatial locating antenna may be disposed within a first housing, and a second portion of the spatial locating device and the second spatial locating antenna may be disposed within a second housing. In certain embodiments, a first IMU may be disposed within the first housing, and a second IMU may be disposed within the second housing. 
     In the illustrated embodiment, the obstacle detection system  12  of the control system of the vehicle  10  includes a steering control system  46  configured to control a direction of movement of the autonomous agricultural vehicle  10 , and a speed control system  48  configured to control a speed of the autonomous agricultural vehicle  10 . In addition, the obstacle detection system  12  includes the controller  44 , which is communicatively coupled to the spatial locating device  38 , to the steering control system  46 , to the speed control system  48 , to the lidar sensor  20 , and to the radar sensor  22 . The controller  44  is configured to automatically control the agricultural vehicle during certain phases of agricultural operations (e.g., without operator input, with limited operator input, etc.). While the controller is shown as controller the object detection system as well as the control systems of the agricultural vehicle, other embodiments may include a controller for the object detection system and a controller  44  for the control systems of the agricultural vehicle. 
     In certain embodiments, the controller  44  is an electronic controller having electrical circuitry configured to process data from the lidar sensor  20  and the radar sensor  22 , as well as the other components of the control system  36 . In the illustrated embodiment, the controller  44  includes a processor  50 , such as the illustrated microprocessor, and a memory device  52 . The controller  44  may also include one or more storage devices and/or other suitable components. The processor  50  may be used to execute software, such as software for controlling the autonomous agricultural vehicle, software for determining vehicle orientation, and so forth. Moreover, the processor  50  may include multiple microprocessors, one or more “general-purpose” microprocessors, one or more special-purpose microprocessors, and/or one or more application specific integrated circuits (ASICS), or some combination thereof. For example, the processor  50  may include one or more reduced instruction set (RISC) processors. 
     The memory device  52  may include a volatile memory, such as random access memory (RAM), and/or a nonvolatile memory, such as read-only memory (ROM). The memory device  52  may store a variety of information and may be used for various purposes. For example, the memory device  52  may store processor-executable instructions (e.g., firmware or software) for the processor  50  to execute, such as instructions for controlling the autonomous agricultural vehicle, instructions for determining vehicle orientation, and so forth. The storage device(s) (e.g., nonvolatile storage) may include ROM, flash memory, a hard drive, or any other suitable optical, magnetic, or solid-state storage medium, or a combination thereof. The storage device(s) may store data (e.g., sensor data, position data, vehicle geometry data, etc.), instructions (e.g., software or firmware for controlling the autonomous agricultural vehicle, etc.), and any other suitable data. 
     In certain embodiments, the steering control system  46  may include a wheel angle control system, a differential braking system, a torque vectoring system, or a combination thereof. The wheel angle control system may automatically rotate one or more wheels and/or tracks of the autonomous agricultural vehicle (e.g., via hydraulic actuators) to steer the autonomous agricultural vehicle along a desired route (e.g., along the guidance swath, along the swath acquisition path, etc.). By way of example, the wheel angle control system may rotate front wheels/tracks, rear wheels/tracks, and/or intermediate wheels/tracks of the autonomous agricultural vehicle, either individually or in groups. The differential braking system may independently vary the braking force on each lateral side of the autonomous agricultural vehicle to direct the autonomous agricultural vehicle along a path. Similarly, the torque vectoring system may differentially apply torque from an engine to wheels and/or tracks on each lateral side of the autonomous agricultural vehicle, thereby directing the autonomous agricultural vehicle along a path. In further embodiments, the steering control system may include other and/or additional systems to facilitate directing the autonomous agricultural vehicle along a path through the field. 
     In certain embodiments, the speed control system  48  may include an engine output control system, a transmission control system, a braking control system, or a combination thereof. The engine output control system may vary the output of the engine to control the speed of the autonomous agricultural vehicle. For example, the engine output control system may vary a throttle setting of the engine, a fuel/air mixture of the engine, a timing of the engine, other suitable engine parameters to control engine output, or a combination thereof. In addition, the transmission control system may adjust input-output ratio within a transmission to control the speed of the autonomous agricultural vehicle. Furthermore, the braking control system may adjust braking force, thereby controlling the speed of the autonomous agricultural vehicle. In further embodiments, the speed control system may include other and/or additional systems to facilitate adjusting the speed of the autonomous agricultural vehicle. 
     In certain embodiments, the controller  44  may also control operation of an agricultural implement coupled to the autonomous agricultural vehicle. For example, the control system may include an implement control system/implement controller configured to control a steering angle of the implement (e.g., via an implement steering control system having a wheel angle control system and/or a differential braking system) and/or a speed of the autonomous agricultural vehicle/implement system (e.g., via an implement speed control system having a braking control system). In such embodiments, the controller  44  may be communicatively coupled to a control system/controller on the implement via a communication network, such as a controller area network (CAN bus). 
     In the illustrated embodiment, the obstacle detection system  12  includes a user interface  54  communicatively coupled to the controller  44 . The user interface  54  is configured to enable an operator (e.g., standing proximate to the autonomous agricultural vehicle) to control certain parameters associated with operation of the autonomous agricultural vehicle. For example, the user interface  54  may include a switch that enables the operator to configure the autonomous agricultural vehicle for autonomous or manual operation. In addition, the user interface  54  may include a battery cut-off switch, an engine ignition switch, a stop button, or a combination thereof, among other controls. In certain embodiments, the user interface  54  includes a display  56  configured to present information to the operator, such as a graphical representation of a guidance swath, a visual representation of certain parameter(s) associated with operation of the autonomous agricultural vehicle (e.g., fuel level, oil pressure, water temperature, etc.), a visual representation of certain parameter(s) associated with operation of an implement coupled to the autonomous agricultural vehicle (e.g., seed level, penetration depth of ground engaging tools, orientation(s)/position(s) of certain components of the implement, etc.), or a combination thereof, among other information. In certain embodiments, the display  56  may include a touch screen interface that enables the operator to control certain parameters associated with operation of the autonomous agricultural vehicle and/or the implement. 
     In the illustrated embodiment, the control system  36  includes manual controls  58  configured to enable an operator to control the autonomous agricultural vehicle while automatic control is disengaged (e.g., while unloading the autonomous agricultural vehicle from a trailer, etc.). The manual controls  58  may include manual steering control, manual transmission control, manual braking control, or a combination thereof, among other controls. In the illustrated embodiment, the manual controls  58  are communicatively coupled to the controller  44 . The controller  44  is configured to disengage automatic control of the autonomous agricultural vehicle upon receiving a signal indicative of manual control of the autonomous agricultural vehicle. Accordingly, if an operator controls the autonomous agricultural vehicle manually, the automatic control terminates, thereby enabling the operator to control the autonomous agricultural vehicle. 
     In the illustrated embodiment, the agricultural vehicle  10  includes one or more lidar sensors  20  and/or radar sensors  22 . While the lidar sensor  20  and the radar sensor  22  of  FIG. 2  are shown in a configuration (e.g., lidar to the left of radar sensor), this is simply meant to be an example and any suitable configuration may be used. Each sensor  20  and  22  may detect properties of the environment (e.g., agricultural field  14 ) and provide data to the controller  44 . For example, the radar sensor  22  may send radio waves  66  via an antenna  68  into the environment. The radio waves  66  may then interact with the environment. Some of the radio waves may then be reflected due to the obstacle  28 , and the reflected radio waves  66  may be detected by the radar sensor  22  via the antenna  68 . Based on a speed at which the radio waves travel and an amount of time between when the radio waves  66  are sent and received, a distance between the obstacle  28  may be determined and the agricultural vehicle  10  may be determined (e.g., via the controller  44  and/or the sensor  22 ). The radar sensor  22  may send signal(s) to the controller  44  indicative of a distance between the obstacle  28  and the agricultural vehicle  10  (e.g., the determined distance and/or the amount of time between when the radio waves  66  are sent and received). 
     In the illustrated embodiment, the lidar sensor  20  may include one or more lasers  70 . The lidar sensors  20  may send pulses of light  72 , such as infrared (IR) light, colored light, or electromagnetic radiation of any suitable frequency, in various directions to interact with the environment. Some of the light  72  may be reflected due to the obstacle  28  and the laser sensor  20  may receive the reflected light (e.g., via the photodiode  74 ). Based on a speed at which the light  72  travels and an amount of time between when the light  72  is sent and received, a distance between the obstacle  28  and the agricultural vehicle  10  may be determined (e.g., via the controller  44  and/or the sensor  20 ). The lidar sensor  20  may send signal(s) to the controller indicative of a distance between the obstacle  28  and the agricultural vehicle  10  (e.g., the determined distance and/or the amount of time between when the light  72  is sent and the photodetector  74  detects the light  72 ). Moreover, depending on the direction that the light  72  is sent, a direction in which the obstacle  28  is detected may be determined. 
     In certain embodiments, the control system may include other and/or additional controllers/control systems, such as the implement controller/control system discussed above. For example, the implement controller/control system may be configured to control various parameters of an agricultural implement towed by the agricultural vehicle. In certain embodiments, the implement controller/control system may be configured to instruct actuator(s) to adjust a penetration depth of at least one ground engaging tool of the agricultural implement. By way of example, the implement controller/control system may instruct actuator(s) to reduce or increase the penetration depth of each tillage point on a tilling implement, or the implement controller/control system may instruct actuator(s) to engage or disengage each opener disc/blade of a seeding/planting implement from the soil. Furthermore, the implement controller/control system may instruct actuator(s) to transition the agricultural implement between a working position and a transport portion, to adjust a flow rate of product from the agricultural implement, or to adjust a position of a header of the agricultural implement (e.g., a harvester, etc.), among other operations. The agricultural vehicle control system may also include controller(s)/control system(s) for electrohydraulic remote(s), power take-off shaft(s), adjustable hitch(es), or a combination thereof, among other controllers/control systems. 
       FIG. 3  is a flow diagram of a process  82  performed by the processor  50  to create or update the map  76  of  FIG. 2 . At block  84 , the processor  50  may receive lidar sensor data and radar sensor data. As explained above, while a lidar sensor and a radar sensor are used as an example, any combination of sensors suitable may be used. The controller  44  may receive signal(s) from the lidar sensor  20  indicative of the distances and/or directions from the agricultural vehicle to the obstacle  28 . Further, the controller  44  may receive radar sensor data indicating distance to the obstacle  28 . At block  86 , the processor  50  may determine obstacle distance and/or direction based on the radar data. For example, the processor  50  may determine distance and/or direction of the obstacle  28  based on the amount of time between when the radio wave  66  is sent and when the radio wave  66  is received. The radar sensor  22  may provide the distance to the controller  44   
     At block  88 , the processor  50  may create or update the point cloud having data points that correspond to locations of an obstacle based on the lidar sensor data. While the illustrated embodiment includes lidar sensor data, in other embodiments, the point cloud data may be acquired via a stereo camera. In certain embodiments, the lidar sensor  20  may include multiple lasers  70  to send light  72  in multiple directions. The processor  50  may then create or update a set of points in a coordinate system, referred to as a point cloud, based on the distances and/or directions of the light received by the lidar sensor  20 . For example, the processor  50  may determine points in a coordinate system that correspond to the locations from the distances and the direction that the light reflected from the obstacle  28 . 
     At block  90 , the processor  50  may create or update a map  76  based on the obstacle distance and direction. The map  76  may be a coordinate (e.g., Cartesian, Polar, etc.) map (e.g., 1 dimension, 2 dimensions, or 3 dimensions) having cells that correspond to locations on a surface of the agricultural field  14  indicating if a particular area includes an obstacle or not (e.g., an occupancy grid). While the obstacle is shown as an object, in some embodiments, the obstacle may include un-drivable terrain (e.g., steep stream bank or burm, etc.) in addition to objects in the environment. Each grid cell may include a state of obstacle or non-obstacle. Further, each grid cell may be independent of one another and have a prior probability indicating a probability that the respective grid cell had an obstacle (e.g., from prior grid cell data). The processor  50  may determine a height difference by calculation of a gradient (e.g., slopes) between the points of the point cloud. If the height difference (e.g., from lasers sent at various heights) in a given cell associated with the point cloud is greater than neighbor cells, then the processor  50  may determine that an obstacle is occupying the location that corresponds to the grid cell. The processor  50  may determine the height difference by calculation of a gradient (e.g., slopes) between the points of the point cloud. The processor  50  may determine that an obstacle is present if the gradient exceeds a threshold. In some embodiments, the grid cells used to analyze the point cloud from the lidar sensors may be different than the grid cells of the map  76 . For example, a first grid of points from the point cloud may be used to determine height differences between points of the point cloud in determining whether an obstacle is present or not, and a second grid may be used to indicate locations on the surface of the agricultural field  14  that include obstacles or not. Further, while a gradient of points from a point cloud is used as an example, any suitable method may be used to determine whether an obstacle is present in a grid cell. 
     The processor  50  may utilize prior data in conjunction with more recent lidar and radar sensor data to determine the state of each grid cell. For example, each sensor may include a true positive rate and a true negative rate. The processor  50  may associate the lidar sensor data with the lidar true positive and true negative rates and the radar sensor data with the radar true positive and true negative rates. The processor  50  may then identify the grid cell of the location associated with the lidar sensor data and the radar sensor data. The processor  50  may determine a probability of an obstacle being present at the location corresponding to the grid cell based on the true positive and true negative rates, the prior grid cell probability of an obstacle occupying the location corresponding to the grid cell, and the lidar and radar sensor data. For example, the processor  50  may determine the probability of the obstacle being present in the grid cell using Bayes theorem to account for prior cell probability, the probability of the true positive and true negative rates, and the lidar and/or radar sensor data. Bayes&#39; theorem may include: 
     
       
         
           
             
               
                 
                   
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     where P(A|B) is the probability that the obstacle is present given that the sensor detected the obstacle, P(B|A) is the probability that the sensor detected the obstacle previously, P(A) is the true positive rate (e.g., probability that the sensor is correct), P(B) is the probability of the obstacle being detected. 
     In some embodiments, the processor  50  may weigh probabilities of different sensors in determining the map, such as weighing the lidar sensor data, radar sensor data, red-blue-green (RGB) sensor data, based on the respective sensor accuracy. The processor  50  may determine whether the grid cell includes an obstacle or does not include an obstacle by comparing the determined probability to a threshold. If the probability of an obstacle is greater than a threshold probability, the grid cell indicates the cell as an obstacle. The data is sent to a control system to control the operations of the vehicle. 
     In some embodiments, the radar  22  may provide the controller with a distance to the obstacle  28 . The processor  50  may determine that the obstacle  28  is located at a distance. The processor  50  may create an arc of obstacle data in a point cloud format based on the distance. The processor  50  may determine that the area within the arc does not include the obstacle  28 . 
       FIG. 4  is a flow diagram of a process  92  performed by the processor  50  to control the vehicle based on the map of  FIG. 3 . The process  92  may be stored as instructions (e.g., code) in the memory  52  of the agricultural vehicle  10 . While the process  92  is described as being performed by the processor  50 , this is meant to be an example, and any suitable control system may be used to perform the process  92 . At block  94 , the processor  50  may obtain a map based on point cloud data from the lidar sensor and the obstacle distance and/or direction from the radar sensor. In certain embodiments, another control system on the agricultural vehicle  10  may include a processor  50  that performs the process  92 . The controller  52  may send signal(s) to the other control system to perform the process  92 . In some embodiments, the controller  52  may transmit signal(s) via the transceiver  60  to another control system not located on the agricultural vehicle  10 . The other control system may include another controller that performs the process  92  and sends signals to the controller  52  indicative of instructions to enable the controller  52  to control the steering control system  46  and/or speed control system  48 . 
     At block  96 , the processor  50  may compare an operation plan to the map  72  to determine if the current plan is blocked by the detected obstacle on the map  72 . That is, if the lidar sensor  20  and/or radar sensor  22  detects an obstacle, the obstacle may be located on the map. The processor  50  may create a drivable path plan that travels around the detected obstacle based on the location of the obstacle in the map  72 . 
     At block  98 , the processor  50  may send signal(s) to control the agricultural vehicle  10  based on the comparison of the map to the operation plan and/or send an alert to an operator. In certain embodiments, the processor  50  may drive the drivable path plan without input from an operator. In other embodiments, the processor  50  may send the drivable path plan to an operator of a control system to enable the operator to accept or reject the proposed path travel around the obstacle. In some embodiments, the processor  50  my send a set of drivable path plans to enable an operator to select from. For example, the processor  50  may receive a selected drivable path plan and control the vehicle based on the selected plan. The processor  50  may receive a path plotted by the operator and control the vehicle to travel along the plotted path. Further, an operator may view images from an RGB camera on the agricultural vehicle to identify the obstacle and determine whether the obstacle is a drivable obstacle, such as a weed, or a non-drivable obstacle, such as a fence. In some embodiments, the processor  50  may control the agricultural vehicle  10  by sending a signal to stop the agricultural vehicle  10  and wait for feedback from the operator. By controlling the agricultural vehicle  10  in a path that travels around the obstacle, the agricultural vehicle  10  may continue to perform the agricultural operation with reduced operator input while still avoiding contacting non-drivable obstacles. 
     Depending on the sensor, positioning of the sensor may enable the sensor to acquire additional data.  FIG. 5A  and  FIG. 5B  show graphs  100  and  104  of a scanning pattern of data acquired by the lidar detector  20 . The boxes  102  and  106  on each of  FIGS. 5A and 5B  are the approximate vehicle dimensions. Depending on the sensor, some lidar sensors  20  may include a field of view of −15 to 15 degrees from level. Graph  100  shows the scanning pattern acquired by the lidar detector  20  in a level position with respect to the agricultural field  14 . Graph  104  shows the scanning pattern acquired by the lidar detector  20  in a position angled towards the ground. That is, the lidar sensor may be positioned in a downward (e.g., 5-10 degrees) direction to provide a greater resolution of scanning patterns detected by the lidar detector  20  by utilizing a larger percentage of the field of view of the lidar sensor  20  as compared to a lidar sensor  20  positioned level to the agricultural field  14 . 
     While only certain features of the invention have been illustrated and described herein, many modifications and changes will occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.