Abstract: A computing system may provide a model of a robot. The model may be configured to determine simulated motions of the robot based on sets of control parameters. The computing system may also operate the model with multiple sets of control parameters to simulate respective motions of the robot. The computing system may further determine respective scores for each respective simulated motion of the robot, wherein the respective scores are based on constraints associated with each limb of the robot and a goal. The constraints include actuator constraints and joint constraints for limbs of the robot. Additionally, the computing system may select, based on the respective scores, a set of control parameters associated with a particular score. Further, the computing system may modify a behavior of the robot based on the selected set of control parameters to perform a coordinated exertion of forces by actuators of the robot.

Abstract: An example robot includes a first actuator and a second actuator connecting a first portion of a first member of the robot to a second member of the robot. Extension of the first actuator accompanied by retraction of the second actuator causes the first member to roll in a first roll direction. Retraction of the first actuator accompanied by extension of the second actuator causes the first member to roll in a second roll direction. A third actuator connects a second portion of the first member to the second member. Extension of the third actuator accompanied by retraction of both the first and second actuators causes the first member to pitch in a first pitch direction. Retraction of the third actuator accompanied by extension of both the first and second actuators causes the first member to pitch in a second pitch direction.

Abstract: A method for constraining robot autonomy language includes receiving a navigation command to navigate a robot to a mission destination within an environment of the robot and generating a route specification for navigating the robot from a current location in the environment to the mission destination in the environment. The route specification includes a series of route segments. Each route segment in the series of route segments includes a goal region for the corresponding route segment and a constraint region encompassing the goal region. The constraint region establishes boundaries for the robot to remain within while traversing toward the goal region. The route segment also includes an initial path for the robot to follow while traversing the corresponding route segment.

Abstract: A computing system may provide a model of a robot. The model may be configured to determine simulated motions of the robot based on sets of control parameters. The computing system may also operate the model with multiple sets of control parameters to simulate respective motions of the robot. The computing system may further determine respective scores for each respective simulated motion of the robot, wherein the respective scores are based on constraints associated with each limb of the robot and a predetermined goal. The constraints include actuator constraints and joint constraints for limbs of the robot. Additionally, the computing system may select, based on the respective scores, a set of control parameters associated with a particular score. Further, the computing system may modify a behavior of the robot based on the selected set of control parameters to perform a coordinated exertion of forces by actuators of the robot.

Abstract: Methods and apparatus for performing automated inspection of one or more assets in an environment using a mobile robot are provided. The method, comprises defining, within an image captured by a sensor of a robot, a region of interest that includes an asset in an environment of the robot, wherein the asset is associated with an asset identifier, configuring at least one parameter of a computer vision model based on the asset identifier, processing image data within the region of interest using the computer vision model to determine whether an alert should be generated, and outputting the alert when it is determined that the alert should be generated.

Abstract: An example implementation involves receiving measurements from an inertial sensor coupled to the robot and detecting an occurrence of a foot of the legged robot making contact with a surface. The implementation also involves reducing a gain value of an amplifier from a nominal value to a reduced value upon detecting the occurrence. The amplifier receives the measurements from the inertial sensor and provides a modulated output based on the gain value. The implementation further involves increasing the gain value from the reduced value to the nominal value over a predetermined duration of time after detecting the occurrence. The gain value is increased according to a profile indicative of a manner in which to increase the gain value of the predetermined duration of time. The implementation also involves controlling at least one actuator of the legged robot based on the modulated output during the predetermined duration of time.

Abstract: A robot includes a drive system configured to maneuver the robot about an environment and data processing hardware in communication with memory hardware and the drive system. The memory hardware stores instructions that when executed on the data processing hardware cause the data processing hardware to perform operations. The operations include receiving image data of the robot maneuvering in the environment and executing at least one waypoint heuristic. The at least one waypoint heuristic is configured to trigger a waypoint placement on a waypoint map. In response to the at least one waypoint heuristic triggering the waypoint placement, the operations include recording a waypoint on the waypoint map where the waypoint is associated with at least one waypoint edge and includes sensor data obtained by the robot. The at least one waypoint edge includes a pose transform expressing how to move between two waypoints.

Abstract: An example implementation involves receiving measurements from an inertial sensor coupled to the robot and detecting an occurrence of a foot of the legged robot making contact with a surface. The implementation also involves reducing a gain value of an amplifier from a nominal value to a reduced value upon detecting the occurrence. The amplifier receives the measurements from the inertial sensor and provides a modulated output based on the gain value. The implementation further involves increasing the gain value from the reduced value to the nominal value over a predetermined duration of time after detecting the occurrence. The gain value is increased according to a profile indicative of a manner in which to increase the gain value of the predetermined duration of time. The implementation also involves controlling at least one actuator of the legged robot based on the modulated output during the predetermined duration of time.

Abstract: The disclosure provides a method for generating a joint command. The method includes receiving a maneuver script including a plurality of maneuvers for a legged robot to perform where each maneuver is associated with a cost. The method further includes identifying that two or more maneuvers of the plurality of maneuvers of the maneuver script occur at the same time instance. The method also includes determining a combined maneuver for the legged robot to perform at the time instance based on the two or more maneuvers and the costs associated with the two or more maneuvers. The method additionally includes generating a joint command to control motion of the legged robot at the time instance where the joint command commands a set of joints of the legged robot. Here, the set of joints correspond to the combined maneuver.

Abstract: A robot includes a drive system configured to maneuver the robot about an environment and data processing hardware in communication with memory hardware and the drive system. The memory hardware stores instructions that when executed on the data processing hardware cause the data processing hardware to perform operations. The operations include receiving image data of the robot maneuvering in the environment and executing at least one waypoint heuristic. The at least one waypoint heuristic is configured to trigger a waypoint placement on a waypoint map. In response to the at least one waypoint heuristic triggering the waypoint placement, the operations include recording a waypoint on the waypoint map where the waypoint is associated with at least one waypoint edge and includes sensor data obtained by the robot. The at least one waypoint edge includes a pose transform expressing how to move between two waypoints.

Abstract: An example method may include i) detecting a disturbance to a gait of a robot, where the gait includes a swing state and a step down state, the swing state including a target swing trajectory for a foot of the robot, and where the target swing trajectory includes a beginning and an end; and ii) based on the detected disturbance, causing the foot of the robot to enter the step down state before the foot reaches the end of the target swing trajectory.

Abstract: The disclosure provides a method for generating a joint command. The method includes receiving a maneuver script including a plurality of maneuvers for a legged robot to perform where each maneuver is associated with a cost. The method further includes identifying that two or more maneuvers of the plurality of maneuvers of the maneuver script occur at the same time instance. The method also includes determining a combined maneuver for the legged robot to perform at the time instance based on the two or more maneuvers and the costs associated with the two or more maneuvers. The method additionally includes generating a joint command to control motion of the legged robot at the time instance where the joint command commands a set of joints of the legged robot. Here, the set of joints correspond to the combined maneuver.

Abstract: A robot includes a drive system configured to maneuver the robot about an environment and data processing hardware in communication with memory hardware and the drive system. The memory hardware stores instructions that when executed on the data processing hardware cause the data processing hardware to perform operations. The operations include receiving image data of the robot maneuvering in the environment and executing at least one waypoint heuristic. The at least one waypoint heuristic is configured to trigger a waypoint placement on a waypoint map. In response to the at least one waypoint heuristic triggering the waypoint placement, the operations include recording a waypoint on the waypoint map where the waypoint is associated with at least one waypoint edge and includes sensor data obtained by the robot. The at least one waypoint edge includes a pose transform expressing how to move between two waypoints.

Abstract: An example method may include i) detecting a disturbance to a gait of a robot, where the gait includes a swing state and a step down state, the swing state including a target swing trajectory for a foot of the robot, and where the target swing trajectory includes a beginning and an end; and ii) based on the detected disturbance, causing the foot of the robot to enter the step down state before the foot reaches the end of the target swing trajectory.

Abstract: An example method may include i) determining a first distance between a pair of feet of a robot at a first time, where the pair of feet is in contact with a ground surface; ii) determining a second distance between the pair of feet of the robot at a second time, where the pair of feet remains in contact with the ground surface from the first time to the second time; iii) comparing a difference between the determined first and second distances to a threshold difference; iv) determining that the difference between determined first and second distances exceeds the threshold difference; and v) based on the determination that the difference between the determined first and second distances exceeds the threshold difference, causing the robot to react.

Abstract: The present invention proposes an apparatus for demolding materials produced by means of the processing technique called freeze-casting. More specifically, it addresses to the application of a linear actuator to perform the sliding/extraction of solid-state parts in low-temperature condition from the containers used as a mold for manufacturing parts using freeze-casting. The device allows pressure to be applied to the material to be removed, resulting in ejection. The artifact also allows the displacement of the element with controlled displacement speed, providing the achievement of defect-free materials. System for demolding materials obtained by means of the freeze-casting technique characterized in that it comprises a source of compressed air (1), a pressure regulator filter (2) coupled with a manometer (3), a directional valve (4), an actuator linear (5), a baton (6), a flow regulating valve (7), a fastening means (8), a metallic support (9) and a chamber for receiving the cooled material (10).

Abstract: A method tor controlling a robot includes receiving image data from at least one image sensor. The image data corresponds to an environment about the robot. The method also includes executing a graphical user interface configured to display a scene of the environment based on the image data and receive an input indication indicating selection of a pixel location within the scene. The method also includes determining a pointing vector based on the selection of the pixel location. The pointing vector represents a direction of travel for navigating the robot in the environment. The method also includes transmitting a waypoint command to the robot. The waypoint command when received by the robot causes the robot to navigate to a target location. The target location is based on an intersection between the pointing vector and a terrain estimate of the robot.

Abstract: A method includes receiving, while a robot traverses a building environment, sensor data captured by one or more sensors of the robot. The method includes receiving a building information model (BIM) for the environment that includes semantic information identifying one or more permanent objects within the environment. The method includes generating a plurality of localization candidates for a localization map of the environment. Each localization candidate corresponds to a feature of the environment identified by the sensor data and represents a potential localization reference point. The localization map is configured to localize the robot within the environment when the robot moves throughout the environment.

Abstract: A method for controlling a robot includes receiving image data from at least one image sensor. The image data corresponds to an environment about the robot. The method also includes executing a graphical user interface configured to display a scene of the environment based on the image data and receive an input indication indicating selection of a pixel location within the scene. The method also includes determining a pointing vector based on the selection of the pixel location. The pointing vector represents a direction of travel for navigating the robot in the environment. The method also includes transmitting a waypoint command to the robot. The waypoint command when received by the robot causes the robot to navigate to a target location. The target location is based on an intersection between the pointing vector and a terrain estimate of the robot.

Abstract: An example method may include i) determining a first distance between a pair of feet of a robot at a first time, where the pair of feet is in contact with a ground surface; ii) determining a second distance between the pair of feet of the robot at a second time, where the pair of feet remains in contact with the ground surface from the first time to the second time; iii) comparing a difference between the determined first and second distances to a threshold difference; iv) determining that the difference between determined first and second distances exceeds the threshold difference; and v) based on the determination that the difference between the determined first and second distances exceeds the threshold difference, causing the robot to react.