Patent Description:
Many modern robots and other machines are designed to operate with increased autonomy and are less reliant on well-trained operators to safely operate. Some of these modern robots are manned while others are unmanned. In particular, a variety of unmanned vehicles include unmanned ground vehicles (UGVs), unmanned aerial vehicles (UAVs), unmanned surface vehicles (USVs), unmanned underwater vehicles (UUVs), unmanned spacecraft and the like. The use of unmanned vehicles has grown in recent years and these unmanned vehicles are employed in a wide variety of applications, including both military and civilian uses.

One focus in the field of robotics is in the improvement of autonomy, which often includes multiple examples of robot operation. These examples of robot operation include automatic control of a given robot to support remote human control. Another example is optimization systems (and associated methods) to determine how, for a given robot or set of robots, tasks should be ordered and/or allocated. And yet another example of robot operation is automatic, real-time or near real-time data processing, and exploitation in support of automatic route planning, mission execution and other activities.

Despite advancements, existing autonomy systems are typically configured to address only one example of these activities, thereby focusing its design of the underling autonomy algorithms and software architecture on a narrow mission set. This limits the extensibility of existing autonomy systems, as they are not well-equipped to support the addition of new modules to the autonomy system. Furthermore, existing autonomy systems may or may not be structured for rapid adaptation to new platforms through parameterization.

<CIT>, in accordance with its abstract, describes an alternate destination planner for searching a navigation database in an aircraft and identifying a plurality of alternate destinations at which the aircraft can land in the event of an emergency. For each identified alternate destination, the alternate destination planner calculates an estimated time of arrival (ETA) and an amount of fuel remaining upon arrival at the destination. The calculation of the ETA and the remaining fuel is based on user-modifiable parameters of aircraft speed, aircraft altitude, wind direction and speed, outside air temperature, and the type of routing the aircraft will follow from a diversion point to the alternate destination. The plurality of alternate destinations are displayed to a pilot of the aircraft according to the ETA to each alternate destination, with the closest alternate destination by time listed first. The plurality of alternate destinations are also displayed to the pilot on a map of the surrounding region that is provided to the pilot on a navigation display. A pilot may select and divert to one of the plurality of alternate destinations using a minimal number of keystrokes on a control display unit.

<CIT>, in accordance with its abstract, describes a flight management computer modification that provides a pilot of an aircraft with a list of alternate landing destinations at which he can land the aircraft in case of an emergency on board or due to some reason why he cannot land at an intended destination. Each of the alternate landing destinations is displayed with data regarding the distance between the aircraft's present position and each of the alternate destinations, the estimated time of arrival to fly the aircraft to each of the alternate destinations and an estimate of the fuel remaining on board the aircraft if the aircraft were to land at the alternate destinations. The data allows the pilot to compare the benefits of landing at one of the alternate destinations versus landing at another. The dam is calculated assuming a direct flight from the aircraft's present position to the alternate as well as assuming a missed approach at the intended destination and a flight from the intended destination to the alternate landing destination. The computational time required to produce the data for the pilot is minimized by increasing the size of the integration steps used by the flight management computer to calculate estimated time of arrival and fuel remaining and by using the flight management computer's precalculated values for optimum climb and descent angles.

Therefore it would be desirable to have a system and method that takes into account at least some of the issues discussed above, as well as other possible issues.

There is described herein a method of supporting a robot in response to a contingency event. The method comprises detecting the contingency event during travel of the robot on a route to a destination; and, in response thereto, determining a position of the robot; accessing information about alternate destinations associated with the route; selecting an alternate destination from the alternate destinations based on a time to travel from the position of the robot to the alternate destination, and the information; and outputting an indication of the alternate destination for use in at least one of guidance, navigation or control of the robot to the alternate destination. The route is divided into route segments, and determining the position of the robot includes determining a route segment on which the robot is positioned. The information about the alternate destinations includes a lookup table of the route segments each of which is associated with one or more contingency routes to one or more of the alternate destinations, and selecting the alternate destination includes selecting a contingency route to an alternate destination associated with the route segment in the lookup table. The route is a pre-planned route of the robot that is divided by travel time, distance or percentage of route completion into the route segments and each of at least some of the route segments in the lookup table is associated with a pre-planned contingency route to one of the alternate destinations. Outputting the indication of the alternate destination includes outputting an indication of the pre-panned contingency route to the alternate destination.

Examples of the present disclosure are directed to selection of an alternate destination for a robot in response to a contingency event, and in some examples in which the robot is an aerial robot, this alternate designation may be an alternate landing zone. According to some examples, a contingency event may be detected during travel of a robot on a route to a destination, and this route may be a pre-planned route of the robot. The route may be associated with associated with alternate destinations. Information about these alternate destinations may be accessed and used to select an alternate destination also based on a time to travel from the robot's position to the alternate destination.

The present disclosure thus includes, without limitation, the following examples.

There is provided a method of supporting a robot in response to a contingency event, the method comprising detecting the contingency event during travel of the robot on a route to a destination; and in response thereto, determining a position of the robot; accessing information about alternate destinations associated with the route; selecting an alternate destination from the alternate destinations based on a time to travel from the position of the robot to the alternate destination, and the information; and outputting an indication of the alternate destination for use in at least one of guidance, navigation or control of the robot to the alternate destination.

The time to travel may be determined based on at least one of an attitude of the robot; a distance from the position of the robot to the alternate destination; a velocity of the robot; an altitude of the robot; a state of the robot; a status of the robot; a state of a route to the alternate destination; or a state of the alternate destination.

The route is divided into route segments, and determining the position of the robot includes determining a route segment on which the robot is positioned.

The information about the alternate destinations includes a lookup table of the route segments each of which is associated with one or more contingency routes to one or more of the alternate destinations, and selecting the alternate destination includes selecting a contingency route to an alternate destination associated with the route segment in the lookup table.

Outputting the indication of the alternate destination includes outputting an indication of the contingency route to the alternate destination.

The route is a pre-planned route of the robot that is divided by travel time, distance or percentage of route completion into the route segments, and each of at least some of the route segments in the lookup table may be associated with a pre-planned contingency route to one of the alternate destinations.

The route segment may be in the lookup table associated with multiple contingency routes to respective ones of the alternate destinations, and selecting the alternate destination may include selecting one of the multiple contingency routes to one of the respective ones of the alternate destinations that is the alternate destination.

The multiple contingency routes may be ranked according to a cost metric, and selecting the one of the multiple contingency routes may include selecting a ranked one of the multiple contingency routes to the respective ones of the alternate destinations that is feasible for landing the robot when the contingency event is detected.

The multiple contingency routes may be ranked according to the cost metric that is a function of at least one of travel time, distance, terrain along the multiple contingency routes, a type of the robot, a state of the robot, a status of the robot, or a state of an environment of the robot.

A volume of space may be defined that extends along the route and that is divided into volume segments, and determining the position of the robot may include determining a volume segment in which the robot is positioned, wherein the information about the alternate destinations may include a lookup table of the volume segments each of which is associated with one or more contingency routes to one or more of the alternate destinations, and selecting the alternate destination may include selecting a contingency route to an alternate destination associated with the volume segment in the lookup table, and wherein outputting the indication of the alternate destination may include outputting an indication of the contingency route to the alternate destination.

Determining the position of the robot may include determining the position of the robot in three dimensions.

The alternate destinations may be across a geographic region, the alternate destinations may seed a Voronoi tessellation of the geographic region into cells, and determining the position of the robot may include determining a cell of the Voronoi tessellation in which the robot is positioned, and wherein the information about the alternate destinations may include information that describes the Voronoi tessellation, and selecting the alternate destination may include selecting the alternate destination that seeds the cell in which the robot is positioned.

The alternate destinations may correspond to nodes of a k-dimensional tree in which the alternate destinations are organized by position, and wherein the information about the alternate destinations may include information that describes the k-dimensional tree, and selecting the alternate destination may include performing a nearest neighbor search of the k-dimensional tree to find the alternate destination that is closest to the position of the robot.

The method may further comprise causing the robot to travel to the alternate destination.

The method may further comprise causing the robot to return to the route during travel of the robot to the alternate destination.

There is also provided an apparatus for supporting a robot in response to a contingency event, the apparatus comprising a memory having computer-readable program code stored therein; and processing circuitry configured to access the memory, and execute the computer-readable program code to cause the apparatus to at least perform any of the methods described above.

There is also provided a computer-readable storage medium for supporting a robot in response to a contingency event, the computer-readable storage medium being non-transitory and having computer-readable program code stored therein that, in response to execution by processing circuitry, causes an apparatus to at least perform any of the methods described above.

These and other features, examples, and advantages of the present disclosure will be apparent from a reading of the following detailed description together with the accompanying figures, which are briefly described below. The present disclosure includes any combination of two, three, four or more features or elements set forth in this disclosure, regardless of whether such features or elements are expressly combined or otherwise recited in a specific example described herein. This disclosure is intended to be read holistically such that any separable features or elements of the disclosure, in any of its examples, should be viewed as combinable unless the context of the disclosure clearly dictates otherwise.

It will therefore be appreciated that this Brief Summary is provided merely for purposes of summarizing some examples so as to provide a basic understanding of the disclosure. Accordingly, it will be appreciated that the above described examples are merely examples and should not be construed to narrow the scope of the disclosure in any way. Other examples and advantages will become apparent from the following detailed description taken in conjunction with the accompanying figures which illustrate, by way of example, the principles of some described examples.

Having thus described examples of the disclosure in general terms, reference will now be made to the accompanying figures, which are not necessarily drawn to scale, and wherein:.

Some examples of the present disclosure will now be described more fully hereinafter with reference to the accompanying figures, in which some, but not all examples of the disclosure are shown. Indeed, various examples of the disclosure may be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these examples are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. For example, unless specified otherwise or clear from context, references to first, second or the like should not be construed to imply a particular order. A feature may be described as being above another feature (unless specified otherwise or clear from context) may instead be below, and vice versa; and similarly, features described as being to the left of another feature else may instead be to the right, and vice versa. As used herein, unless specified otherwise or clear from context, the "or" of a set of operands is the "inclusive or" and thereby true if and only if one or more of the operands is true, as opposed to the "exclusive or" which is false when all of the operands are true. Thus, for example, "[A] or [B]" is true if [A] is true, or if [B] is true, or if both [A] and [B] are true. Further, the articles "a" and "an" mean "one or more," unless specified otherwise or clear from context to be directed to a singular form. Furthermore, it should be understood that unless otherwise specified, the terms "data," "content," "digital content," "information," and similar terms may be at times used interchangeably.

Examples of the present disclosure relate generally to robotics and, in particular, to one or more of the design, construction, operation or use of robots. As used herein, a robot is a machine designed and configurable to execute maneuvers in its environment. The robot may be manned or unmanned. The robot may be fully human-controlled, or the robot may be semi-autonomous or autonomous in which at least some of the maneuvers are executed independent of or with minimal human intervention. In some examples, the robot is operable in various modes with various amounts of human control.

A robot designed and configurable to fly may at times be referred to as an aerial robot. A robot designed and configurable to operate with at least some level of autonomy may at times be referred to as an autonomous robot, or an autonomous aerial robot in the case of an autonomous robot that is also designed and configurable to fly. Examples of suitable robots include aerobots, androids, automatons, autonomous vehicles, explosive ordnance disposal robots, hexapods, industrial robots, insect robots, microbots, nanobots, military robots, mobile robots, rovers, service robots, surgical robots, walking robots and the like. Other examples include a variety of unmanned vehicles, including unmanned ground vehicles (UGVs), unmanned aerial vehicles (UAVs), unmanned surface vehicles (USVs), unmanned underwater vehicles (UUVs), unmanned spacecraft and the like. These may include autonomous cars, planes, trains, industrial vehicles, fulfillment center robots, supply-chain robots, robotic vehicles, mine sweepers, and the like.

<FIG> illustrates one type of robot, namely, a UAV <NUM>. As shown, the UAV may include a fuselage <NUM>, wings <NUM> extending from opposing sides of the UAV in a mid-section of the fuselage, and an empennage or tail assembly <NUM> at a rear end of the fuselage. The tail assembly includes a vertical stabilizer <NUM> and two horizontal stabilizers <NUM> extending from opposing sides of the UAV. Rotors <NUM> and <NUM> are mounted to respectively the wings and the end of the tail assembly for lifting and propelling the UAV during flight.

<FIG> illustrates a system <NUM> according to some examples of the present disclosure. The system may include any of a number of different subsystems (each an individual system) for performing one or more functions or operations. As shown, in some examples, the system includes a control station <NUM> and one or more robots <NUM> (e.g., one or more UAVs <NUM>). The control station provides facilities for communication with or control of the one or more robots, such as by wired or wireless data links directly or across one or more networks <NUM>. In some examples, the control station may be a ground station, and not in all cases control the robots. In this regard, the control station may be configured to monitor the robots. The control station may initiate mission, but the control station may not control the robots to maneuver. At times, then, the control station may enable or provide a distributed network/server of software functions.

The robot <NUM> includes a robot management system (RMS) <NUM> and a mission management system (MMS) <NUM>. The RMS is a robot-specific subsystem configured to manage subsystems and other components of the robot. These subsystems and other components include, for example, maneuver controls, landing gear, onboard environmental systems, electrical, pneumatic and hydraulic systems, communications systems, navigation systems and other subsystems and components for controlling operation and maneuvering of the robot. The RMS is configured to accept maneuver commands such as waypoints and/or steering commands, and control the robot to follow those maneuver commands. In the context of a vehicle, the RMS is at times referred to as a vehicle management system (VMS).

The MMS <NUM> is a subsystem configured to manage missions of the robot <NUM>. A mission is a deployment of the robot (one or more robots) to achieve one or more mission objectives. A mission may be decomposed into maneuvers of the robot with optional sensor and/or effector scheduling, and the MMS may execute tasks to manage the robot to execute maneuvers with specific parameters and capabilities. The MMS <NUM> includes subsystems to process sensor data to situational awareness, plan tasks for the robot <NUM> (or multiple robots), coordinate with teams to assign tasks, execute assigned tasks. The MMS is also configured to interface with the RMS <NUM>, and in some examples the control station <NUM>. Although the MMS is shown on the robot <NUM>, the MMS may instead be at the control station; or in some examples, the MMS may be distributed between the robot and the control station.

In some examples, the MMS <NUM> provides a complete, end-to-end autonomy architecture with open system architecture standards and parameterized to allow rapid extension and reapplication to a variety of robots. The flexibility of the MMS enables an operator to code it once, but to apply it anywhere. The MMS may therefore be applied to virtually any robot that applies, or benefits from, autonomy. The MMS may include an adaptable autonomy architecture that is applicable to a variety of robots, including those identified above. A benefit of the MMS is therefore not only in the specific contents, but also in the specific details of the architecture, its subroutines, and in the interfaces between those subroutines and other systems/devices that support rapid extensibility and adaptability of the MMS to a variety of domains.

<FIG> more particularly illustrates the MMS <NUM> according to some examples of the present disclosure. The MMS may include any of a number of different subsystems (each an individual system) for performing one or more functions or operations. As shown, in some examples, the MMS includes an interface subsystem <NUM>, a situational awareness subsystem <NUM>, a mission planning subsystem <NUM>, a mission coordination subsystem <NUM>, and a mission execution subsystem <NUM>. As suggested above, in some examples, the subsystems of the MMS may be on the robot <NUM>, at the control station <NUM>, or distributed between the robot and the control station. The subsystems may be configured to communicate with one another directly, over a communication bus <NUM>, or across the network(s) <NUM> in examples in which the MMS is distributed between the robot and the control station.

The subsystems enable the MMS <NUM> of the robot <NUM> to interface with the system <NUM>, perform situational awareness, plan a mission including a plurality of tasks, coordinate the plurality of tasks and thereby the mission with other robots <NUM>, and execute the mission. For example, the MMS may use the interface subsystem <NUM> to interface with various sensors onboard the robot, the RMS <NUM>, the control station <NUM> and/or other robots. The MMS may use the situational awareness subsystem <NUM> to acquire sensor data and maintain an awareness of the state of the environment in which the robot is operating. The MMS may use the mission planning subsystem <NUM> to plan a mission including or associated with a plurality of tasks, and which may incorporate rules of engagement, tactics and other constraints on operations. The MMS may likewise use the mission planning subsystem to dynamically replan a mission in which changes to the mission are made in real-time or near real-time as the mission is executed. The MMS may use the mission coordination subsystem <NUM> to coordinate the plurality of tasks of the mission with other robots and users, where agreed-upon tasks may then be executed by the MMS using the mission execution subsystem <NUM>.

According to some examples of the present disclosure, the MMS <NUM> is also configured to implement software functionality or functionalities (at times referred to as services) during a mission to support the robot <NUM> (in particular an aerial robot) in response to a contingency event. During a mission, the robot may take a path, and this path may be described by a series of waypoints that define a route the robot will travel. The robot travels with a velocity (speed and direction of motion), and the series of waypoints and velocities at that define the route with respect to time defines a trajectory of the robot (at times referred to as a track of the robot). <FIG> illustrates a scenario <NUM> in which the robot is executing a mission in which the robot is to travel on a route <NUM> to a destination <NUM>, according to some examples.

<FIG> is a diagram of services <NUM> that may be implemented by the MMS <NUM> for supporting the robot <NUM> (in particular an aerial robot) in response to a contingency event, according to some examples. As shown, the services may include a manager <NUM> service, a contingency monitor <NUM> service and a destination selection <NUM> service. In some examples, the manager service, contingency monitor service and destination selection service may be implemented by the mission execution subsystem <NUM> of the MMS.

According to some examples, the manager <NUM> service is configured to manage execution of a mission including a plurality of tasks, and which includes travel of the robot on a route <NUM> to a destination <NUM>. The contingency monitor <NUM> service is configured to monitor for contingency events during the mission. The contingency monitor service is configured to detect a contingency event, and report the contingency event to the manager service. In response, the manager service is configured to call on the destination selection <NUM> service to provide an indication of an alternate destination <NUM>. The manager service is configured to use the indication of the alternate destination in at least one of guidance, navigation or control of the robot <NUM> to the alternate destination; and in some examples, the manager service is configured to cause the robot to travel to the alternate destination. The destination and alternate destination may be expressed in a number of different manners. In some examples in which the robot is an aerial robot, the destination and alternate destination may be expressed as zones in which the aerial robot may land, i.e., landing zones.

As also shown, in various examples, the destination selection <NUM> service includes one or more sub-services (each an individual service) such as a selection <NUM> service configured to select the alternate destination <NUM> from alternate destinations associated with the route <NUM>. In particular, the selection service is configured to determine a position <NUM> of the robot, and access information <NUM> about alternate destinations associated with the route. The selection service is configured to select the alternate destination from the alternate destinations based on a time to travel from the position of the robot <NUM> to the alternate destination, and the information.

In various examples, the time to travel is expressed as or otherwise determined based on input data. Examples of suitable input data include an attitude of the robot <NUM>, a distance from the position <NUM> of the robot to the alternate destination <NUM>, a velocity of the robot, an altitude of the robot, a state of the robot, a status of the robot, a state of a route to the alternate destination, or a state of the alternate destination. In some examples, at least some of the input data may be provided by or determined from data provided by various sensors onboard the robot, the RMS <NUM> and/or the control station <NUM>, which may interface with the MMS <NUM> using the interface subsystem <NUM>.

The selection <NUM> service may select the alternate destination <NUM> from the alternate destinations associated with the route <NUM> in any of a number of different manners. According to a brute force approach, for example, the selection service may determine routes from the position <NUM> to respective ones of the alternate destinations, estimate travel times for (times to travel) the routes and select one of the routes based on the travel times as estimated. In some of these examples, the selected one of the routes is the one of the routes with a minimum of travel times.

According to another approach, <FIG> illustrates a route discretization <NUM> in which the route <NUM> is divided into route segments <NUM>, according to some examples. In some of these examples, the selection <NUM> service configured to determine the position <NUM> of the robot <NUM> includes the selection service configured to determine a route segment <NUM> on which the robot is positioned. In some of these examples, the information <NUM> about the alternate destinations includes a lookup table <NUM> of the route segments each of which is associated with one or more contingency routes <NUM> to one or more of the alternate destinations. In some examples, the lookup table <NUM> may be expressed in a tree structure such as a k-dimensional tree, an AABB (axis-aligned bounding boxes) tree or the like, which may enable an efficient query of the lookup table.

In some examples, the selection <NUM> service is configured to select a contingency route <NUM> to an alternate destination <NUM> associated with the route segment <NUM> in the lookup table, and output an indication of the contingency route to the alternate destination.

In some further examples, the route <NUM> is a pre-planned route of the robot <NUM> that is divided by travel time, distance or percentage of route completion into the route segments <NUM>, and each of at least some of the route segments in the lookup table <NUM> is associated with a pre-planned contingency route <NUM> to one of the alternate destinations <NUM>. Additionally or alternatively, the route segment <NUM> may be in the lookup table associated with multiple contingency routes to respective ones of the alternate destinations. An example of entries in the lookup table for three segments may include the following:.

In some of these examples, the selection <NUM> service is configured to select one of the multiple contingency routes to one of the respective ones of the alternate destinations that is the alternate destination.

In some even further examples, the multiple contingency routes <NUM> (e.g., Route <NUM>, Route <NUM>) are ranked according to a cost metric. Examples of a suitable cost metric include a cost metric that is a function of at least one of travel time, distance, terrain along the multiple contingency routes, a type of the robot <NUM>, a state of the robot, a status of the robot, or a state of an environment of the robot. In some of these examples, the selection <NUM> service is configured to select a ranked one (e.g., highest ranked one) of the multiple contingency routes to the respective ones of the alternate destinations <NUM> that is feasible for landing the robot when the contingency event is detected.

In various examples, the selection <NUM> service may determine the position <NUM> of the robot <NUM> in two dimensions (2D) or in in three dimensions (3D). In the 3D case, for example, the route discretization <NUM> may be a top view of the route <NUM>, where a volume of space <NUM> is defined that extends along the route and that is divided into the route segments <NUM> that are volume segments. In some of these examples, the selection <NUM> service configured to determine the position <NUM> of the robot <NUM> includes the selection service configured to determine the route segment <NUM> that is a volume segment in which the robot is positioned. Also in some of these examples, similar to before, the information <NUM> about the alternate destinations <NUM> includes the lookup table <NUM> of the volume segments each of which is associated with one or more contingency routes <NUM> to one or more of the alternate destinations. Also similar to before, the selection service may be configured to selecting the contingency route <NUM> to the alternate destination associated with the volume segment in the lookup table, and output the indication of the contingency route to the alternate destination.

<FIG> illustrates a Voronoi tessellation <NUM> of a geographic region <NUM> including the alternate destinations <NUM>, according to some examples. As shown, in some examples, the alternate destinations are across the geographic region, and seed the Voronoi tessellation of the geographic region into cells <NUM>. In some of these examples, the selection <NUM> service configured to determine the position <NUM> of the robot <NUM> includes the selection service configured to determine a cell of the Voronoi tessellation in which the robot is positioned. Also in some of these examples, the information <NUM> about the alternate destinations includes information <NUM> that describes the Voronoi tessellation, and the selection service is configured to select the alternate destination that seeds the cell in which the robot is positioned.

<FIG> illustrates a k-dimensional tree nearest neighbor <NUM> in which the alternate destinations <NUM> correspond to nodes <NUM> of a k-dimensional tree <NUM> in which the alternate destinations are organized by position, according to some examples. In some of these examples, the information <NUM> about the alternate destinations includes information <NUM> that describes the k-dimensional tree. Also in some of these examples, the selection <NUM> service configured to select the alternate destination includes the selection service configured to perform a nearest neighbor search of the k-dimensional tree to find the alternate destination that is closest to the position <NUM> of the robot <NUM>.

Returning to <FIG>, again, the destination selection <NUM> service of the MMS <NUM> may provide an indication of an alternate destination <NUM> to the manager <NUM> service in response to detection of a contingency event by the contingency monitor <NUM> service. The manager service may use the indication of the alternate destination in at least one of guidance, navigation or control of the robot <NUM> to the alternate destination. In some examples, the manager service is configured to cause the robot to travel to the alternate destination. In some further examples, the manager service is configured to cause the robot to return to the route <NUM> during travel of the robot to the alternate destination. This may include the MMS configured to send one or more maneuver commands to the RMS <NUM> to control the robot to follow the maneuver commands and thereby travel to the alternate destination, and in some examples return to the route.

<FIG> are flowcharts illustrating various steps in a method <NUM> of supporting an aerial robot <NUM> in response to a contingency event, according to examples of the present disclosure. As shown at block <NUM> of <FIG>, the method includes detecting the contingency event during travel of the robot on a route <NUM> to a destination <NUM>. In response, the method includes determining a position <NUM> of the robot, and accessing information <NUM> about alternate destinations <NUM> associated with the route, as shown at blocks <NUM> and <NUM>.

The method <NUM> includes selecting an alternate destination <NUM> from the alternate destinations based on a time to travel from the position of the robot <NUM> to the alternate destination, and the information <NUM>, as shown at block <NUM>. In various examples, the time to travel is determined based on input data such as at least one of an attitude of the robot <NUM>, a distance from the position <NUM> of the robot to the alternate destination <NUM>, a velocity of the robot, an altitude of the robot, a state of the robot, a status of the robot, a state of a route to the alternate destination, or a state of the alternate destination. The method also includes outputting an indication of the alternate destination for use in at least one of guidance, navigation or control of the robot to the alternate destination, as shown at block <NUM>.

In some examples, the route <NUM> is divided into route segments <NUM>, and determining the position <NUM> of the robot <NUM> at block <NUM> includes determining a route segment <NUM> on which the robot is positioned. In some of these examples, the information <NUM> about the alternate destinations <NUM> includes a lookup table <NUM> of the route segments each of which is associated with one or more contingency routes <NUM> to one or more of the alternate destinations. Selecting the alternate destination at block <NUM>, then, includes selecting a contingency route <NUM> to an alternate destination associated with the route segment in the lookup table, and outputting the indication of the alternate destination at block <NUM> includes outputting an indication of the contingency route to the alternate destination.

In some further examples, the route <NUM> is a pre-planned route of the robot <NUM> that is divided by travel time, distance or percentage of route completion into the route segments <NUM>, and each of at least some of the route segments in the lookup table <NUM> is associated with a pre-planned contingency route <NUM> to one of the alternate destinations <NUM>. Additionally or alternatively, in some further examples, the route segment <NUM> is in the lookup table associated with multiple contingency routes to respective ones of the alternate destinations. In some of these examples, selecting the alternate destination at block <NUM> includes selecting one of the multiple contingency routes to one of the respective ones of the alternate destinations that is the alternate destination.

In some even further examples, the multiple contingency routes <NUM> are ranked according to a cost metric. Examples of a suitable cost metric include a cost metric that is a function of at least one of travel time, distance, terrain along the multiple contingency routes, a type of the robot <NUM>, a state of the robot, a status of the robot, or a state of an environment of the robot. In some of these examples, selecting the one of the multiple contingency routes at block <NUM> includes selecting a ranked one of the multiple contingency routes to the respective ones of the alternate destinations <NUM> that is feasible for landing the robot when the contingency event is detected.

In some examples, determining the position <NUM> of the robot <NUM> at block <NUM> includes determining the position of the robot in three dimensions.

In some examples, a volume of space <NUM> is defined that extends along the route <NUM> and that is divided into the route segments <NUM> that are volume segments. In some of these examples, determining the position <NUM> of the robot <NUM> at block <NUM> includes determining the route segment <NUM> that is a volume segment in which the robot is positioned. Also in some of these examples, the information <NUM> about the alternate destinations <NUM> includes a lookup table <NUM> of the volume segments each of which is associated with one or more contingency routes <NUM> to one or more of the alternate destinations. Selecting the alternate destination at block <NUM> includes selecting a contingency route <NUM> to an alternate destination associated with the volume segment in the lookup table, and outputting the indication of the alternate destination at block <NUM> includes outputting an indication of the contingency route to the alternate destination.

In some examples, the alternate destinations <NUM> are across a geographic region <NUM>, and seed a Voronoi tessellation <NUM> of the geographic region into cells <NUM>. In some of these examples, determining the position <NUM> of the robot <NUM> at block <NUM> includes determining a cell of the Voronoi tessellation in which the robot is positioned. Also in some of these examples, the information <NUM> about the alternate destinations includes information <NUM> that describes the Voronoi tessellation, and selecting the alternate destination at block <NUM> includes selecting the alternate destination that seeds the cell in which the robot is positioned.

In some examples, the alternate destinations <NUM> correspond to nodes <NUM> of a k-dimensional tree <NUM> in which the alternate destinations are organized by position. In some of these examples, the information <NUM> about the alternate destinations includes information <NUM> that describes the k-dimensional tree. Also in some of these examples, selecting the alternate destination at block <NUM> includes performing a nearest neighbor search of the k-dimensional tree to find the alternate destination that is closest to the position <NUM> of the robot <NUM>.

As shown at block <NUM>, in some examples, the method <NUM> further includes causing the robot <NUM> to travel to the alternate destination <NUM>. And in some further examples, the method includes causing the robot <NUM> to return to the route <NUM> during travel of the robot to the alternate destination <NUM>, as shown at block <NUM>.

According to examples of the present disclosure, the MMS <NUM> and its subsystems including the interface subsystem <NUM>, situational awareness subsystem <NUM>, mission planning subsystem <NUM>, mission coordination subsystem <NUM> and mission execution subsystem <NUM> may be implemented by various means. Means for implementing the MMS and its subsystems may include hardware, alone or under direction of one or more computer programs from a computer-readable storage medium. In some examples, one or more apparatuses may be configured to function as or otherwise implement the MMS and its subsystems shown and described herein. In examples involving more than one apparatus, the respective apparatuses may be connected to or otherwise in communication with one another in a number of different manners, such as directly or indirectly via a wired or wireless network or the like.

<FIG> illustrates an apparatus <NUM> according to some examples of the present disclosure. Generally, an exemplary apparatus may comprise, include or be embodied in one or more fixed or portable electronic devices. The apparatus may include one or more of each of a number of components such as, for example, processing circuitry <NUM> (e.g., processor unit) connected to a memory <NUM> (e.g., storage device).

The processing circuitry <NUM> may be composed of one or more processors alone or in combination with one or more memories. The processing circuitry may be any piece of computer hardware that is capable of processing information such as, for example, data, computer programs and/or other suitable electronic information. The processing circuitry is composed of a collection of electronic circuits some of which may be packaged as an integrated circuit or multiple interconnected integrated circuits (an integrated circuit at times more commonly referred to as a "chip"). The processing circuitry may be configured to execute computer programs, which may be stored onboard the processing circuitry or otherwise stored in the memory <NUM> (of the same or another apparatus).

The processing circuitry <NUM> may be a number of processors, a multi-core processor or some other type of processor, depending on the particular implementation. Further, the processing circuitry may be implemented using a number of heterogeneous processor systems in which a main processor is present with one or more secondary processors on a single chip. As another illustrative example, the processing circuitry may be a symmetric multi-processor system containing multiple processors of the same type. In yet another example, the processing circuitry may be embodied as or otherwise include one or more ASICs, FPGAs or the like. Thus, although the processing circuitry may be capable of executing a computer program to perform one or more functions, the processing circuitry of various examples may be capable of performing one or more functions without the aid of a computer program. In either instance, the processing circuitry may be appropriately programmed to perform functions or operations according to examples of the present disclosure.

The memory <NUM> may be any piece of computer hardware that is capable of storing information such as, for example, data, computer programs (e.g., computer-readable program code <NUM>) and/or other suitable information either on a temporary basis and/or a permanent basis. The memory may include volatile and/or non-volatile memory, and may be fixed or removable. Examples of suitable memory include random access memory (RAM), read-only memory (ROM), a hard drive, a flash memory, a thumb drive, a removable computer diskette, an optical disk, a magnetic tape or some combination of the above. Optical disks may include compact disk - read only memory (CD-ROM), compact disk - read/write (CD-R/W), DVD or the like. In various instances, the memory may be referred to as a computer-readable storage medium. The computer-readable storage medium is a non-transitory device capable of storing information, and is distinguishable from computer-readable transmission media such as electronic transitory signals capable of carrying information from one location to another. Computer-readable medium as described herein may refer to a computer-readable storage medium or computer-readable transmission medium.

In addition to the memory <NUM>, the processing circuitry <NUM> may also be connected to one or more interfaces for displaying, transmitting and/or receiving information. The interfaces may include a communications interface <NUM> (e.g., communications unit) and/or one or more user interfaces. The communications interface may be configured to transmit and/or receive information, such as to and/or from other apparatus(es), network(s) or the like. The communications interface may be configured to transmit and/or receive information by physical (wired) and/or wireless communications links. Examples of suitable communication interfaces include a network interface controller (NIC), wireless NIC (WNIC) or the like.

The user interfaces may include a display <NUM> and/or one or more user input interfaces <NUM> (e.g., input/output unit). The display may be configured to present or otherwise display information to a user, suitable examples of which include a liquid crystal display (LCD), light-emitting diode display (LED), plasma display panel (PDP) or the like. The user input interfaces may be wired or wireless, and may be configured to receive information from a user into the apparatus, such as for processing, storage and/or display. Suitable examples of user input interfaces include a microphone, image or video capture device, keyboard or keypad, joystick, touch-sensitive surface (separate from or integrated into a touchscreen), biometric sensor or the like. The user interfaces may further include one or more interfaces for communicating with peripherals such as printers, scanners or the like.

As indicated above, program code instructions may be stored in memory, and executed by processing circuitry that is thereby programmed, to implement functions of the systems, subsystems, tools and their respective elements described herein. As will be appreciated, any suitable program code instructions may be loaded onto a computer or other programmable apparatus from a computer-readable storage medium to produce a particular machine, such that the particular machine becomes a means for implementing the functions specified herein. These program code instructions may also be stored in a computer-readable storage medium that can direct a computer, a processing circuitry or other programmable apparatus to function in a particular manner to thereby generate a particular machine or particular article of manufacture. The instructions stored in the computer-readable storage medium may produce an article of manufacture, where the article of manufacture becomes a means for implementing functions described herein. The program code instructions may be retrieved from a computer-readable storage medium and loaded into a computer, processing circuitry or other programmable apparatus to configure the computer, processing circuitry or other programmable apparatus to execute operations to be performed on or by the computer, processing circuitry or other programmable apparatus.

Retrieval, loading and execution of the program code instructions may be performed sequentially such that one instruction is retrieved, loaded and executed at a time. In some examples, retrieval, loading and/or execution may be performed in parallel such that multiple instructions are retrieved, loaded, and/or executed together. Execution of the program code instructions may produce a computer-implemented process such that the instructions executed by the computer, processing circuitry or other programmable apparatus provide operations for implementing functions described herein.

Execution of instructions by a processing circuitry, or storage of instructions in a computer-readable storage medium, supports combinations of operations for performing the specified functions. In this manner, an apparatus <NUM> may include a processing circuitry <NUM> and a computer-readable storage medium or memory <NUM> coupled to the processing circuitry, where the processing circuitry is configured to execute computer-readable program code <NUM> stored in the memory. It will also be understood that one or more functions, and combinations of functions, may be implemented by special purpose hardware-based computer systems and/or processing circuitry which perform the specified functions, or combinations of special purpose hardware and program code instructions.

Claim 1:
A method (<NUM>) of supporting a robot (<NUM>) in response to a contingency event, the method comprising:
detecting (<NUM>) the contingency event during travel of the robot on a route (<NUM>) to a destination (<NUM>); and in response thereto,
determining (<NUM>) a position (<NUM>) of the robot;
accessing (<NUM>) information (<NUM>) about alternate destinations (<NUM>) associated with the route;
selecting (<NUM>) an alternate destination from the alternate destinations based on a time to travel from the position of the robot to the alternate destination, and the information; and
outputting (<NUM>) an indication of the alternate destination for use in at least one of guidance, navigation or control of the robot to the alternate destination; and wherein:
the route (<NUM>) is divided into route segments (<NUM>), and determining (<NUM>) the position (<NUM>) of the robot (<NUM>) includes determining a route segment (<NUM>) on which the robot is positioned;
the information (<NUM>) about the alternate destinations (<NUM>) includes a lookup table (<NUM>) of the route segments each of which is associated with one or more contingency routes (<NUM>) to one or more of the alternate destinations, and selecting (<NUM>) the alternate destination includes selecting a contingency route (<NUM>) to an alternate destination associated with the route segment in the lookup table;
the route (<NUM>) is a pre-planned route of the robot (<NUM>) that is divided by travel time, distance or percentage of route completion into the route segments (<NUM>), and each of at least some of the route segments in the lookup table (<NUM>) is associated with a pre-planned contingency route (<NUM>) to one of the alternate destinations (<NUM>); and
outputting (<NUM>) the indication of the alternate destination includes outputting an indication of the pre-planned contingency route to the alternate destination.