Abstract: A method of constrained mobility mapping includes receiving from at least one sensor of a robot at least one original set of sensor data and a current set of sensor data. Here, each of the at least one original set of sensor data and the current set of sensor data corresponds to an environment about the robot. The method further includes generating a voxel map including a plurality of voxels based on the at least one original set of sensor data. The plurality of voxels includes at least one ground voxel and at least one obstacle voxel. The method also includes generating a spherical depth map based on the current set of sensor data and determining that a change has occurred to an obstacle represented by the voxel map based on a comparison between the voxel map and the spherical depth map. The method additional includes updating the voxel map to reflect the change to the obstacle.

Abstract: Systems and methods are described for instructing performance of a localization and an action by a mobile robot based on composite data. A system may obtain satellite-based position data and one or more of odometry data or point cloud data. The system may generate composite data by merging the satellite-based position data and the one or more of the odometry data or the point cloud data. The system may instruct performance of a localization by the mobile robot based on the composite data. Based on the localization by the mobile robot, the system may identify an action and instruct performance of the action by a mobile robot.

Abstract: A computer-implemented method when executed by data processing hardware of a legged robot causes the data processing hardware to perform operations including receiving sensor data corresponding to an area including at least a portion of a docking station. The operations include determining an estimated pose for the docking station based on an initial pose of the legged robot relative to the docking station. The operations include identifying one or more docking station features from the received sensor data. The operations include matching the one or more identified docking station features to one or more known docking station features. The operations include adjusting the estimated pose for the docking station to a corrected pose for the docking station based on an orientation of the one or more identified docking station features that match the one or more known docking station features.

Abstract: A computer-implemented method when executed by data processing hardware of a legged robot causes the data processing hardware to perform operations including receiving sensor data corresponding to an area including at least a portion of a docking station. The operations include determining an estimated pose for the docking station based on an initial pose of the legged robot relative to the docking station. The operations include identifying one or more docking station features from the received sensor data. The operations include matching the one or more identified docking station features to one or more known docking station features. The operations include adjusting the estimated pose for the docking station to a corrected pose for the docking station based on an orientation of the one or more identified docking station features that match the one or more known docking station features.

Abstract: Systems and methods are described for detecting changes at a location based on image data by a mobile robot. A system can instruct navigation of the mobile robot to a location. For example, the system can instruct navigation to the location as part of an inspection mission. The system can obtain input identifying a change detection. Based on the change detection and obtained image data associated with the location, the system can perform the change detection and detect a change associated with the location. For example, the system can perform the change detection based on one or more regions of interest of the obtained image data. Based on the detected change and a reference model, the system can determine presence of an anomaly condition in the obtained image data.

Abstract: Systems and methods are described for reacting to a feature in an environment of a robot based on a classification of the feature. A system can detect the feature in the environment using a first sensor on the robot. For example, the system can detect the feature using a feature detection system based on sensor data from a camera. The system can detect a mover in the environment using a second sensor on the robot. For example, the system can detect the mover using a mover detection system based on sensor data from a lidar sensor. The system can fuse the data from detecting the feature and detecting the mover to produce fused data. The system can classify the feature based on the fused data and react to the feature based on classifying the feature.

Abstract: A computer-implemented method executed by data processing hardware of a robot causes the data processing hardware to perform operations. The operations include receiving a sensor pointing command that commands the robot to use a sensor to capture sensor data of a location in an environment of the robot. The sensor is disposed on the robot. The operations include determining, based on an orientation of the sensor relative to the location, a direction for pointing the sensor toward the location, and an alignment pose of the robot to cause the sensor to point in the direction toward the location. The operations include commanding the robot to move from a current pose to the alignment pose. After the robot moves to the alignment pose and the sensor is pointing in the direction toward the location, the operations include commanding the sensor to capture the sensor data of the location in the environment.

Abstract: A method of constrained mobility mapping includes receiving from at least one sensor of a robot at least one original set of sensor data and a current set of sensor data. Here, each of the at least one original set of sensor data and the current set of sensor data corresponds to an environment about the robot. The method further includes generating a voxel map including a plurality of voxels based on the at least one original set of sensor data. The plurality of voxels includes at least one ground voxel and at least one obstacle voxel. The method also includes generating a spherical depth map based on the current set of sensor data and determining that a change has occurred to an obstacle represented by the voxel map based on a comparison between the voxel map and the spherical depth map. The method additional includes updating the voxel map to reflect the change to the obstacle.

Abstract: A method of constrained mobility mapping includes receiving from at least one sensor of a robot at least one original set of sensor data and a current set of sensor data. Here, each of the at least one original set of sensor data and the current set of sensor data corresponds to an environment about the robot. The method further includes generating a voxel map including a plurality of voxels based on the at least one original set of sensor data. The plurality of voxels includes at least one ground voxel and at least one obstacle voxel. The method also includes generating a spherical depth map based on the current set of sensor data and determining that a change has occurred to an obstacle represented by the voxel map based on a comparison between the voxel map and the spherical depth map. The method additional includes updating the voxel map to reflect the change to the obstacle.

Abstract: A computer-implemented method when executed by data processing hardware of a legged robot causes the data processing hardware to perform operations including receiving sensor data corresponding to an area including at least a portion of a docking station. The operations include determining an estimated pose for the docking station based on an initial pose of the legged robot relative to the docking station. The operations include identifying one or more docking station features from the received sensor data. The operations include matching the one or more identified docking station features to one or more known docking station features. The operations include adjusting the estimated pose for the docking station to a corrected pose for the docking station based on an orientation of the one or more identified docking station features that match the one or more known docking station features.

Abstract: A method of constrained mobility mapping includes receiving from at least one sensor of a robot at least one original set of sensor data and a current set of sensor data. Here, each of the at least one original set of sensor data and the current set of sensor data corresponds to an environment about the robot. The method further includes generating a voxel map including a plurality of voxels based on the at least one original set of sensor data. The plurality of voxels includes at least one ground voxel and at least one obstacle voxel. The method also includes generating a spherical depth map based on the current set of sensor data and determining that a change has occurred to an obstacle represented by the voxel map based on a comparison between the voxel map and the spherical depth map. The method additional includes updating the voxel map to reflect the change to the obstacle.

Abstract: A method for imaging a moving object includes scanning a predetermined area with at least one distance sensor to form an image of a structure of a moving object using a safe sensing time window to periodically refresh the image. The images of the structure are compared to a known model of the structure to estimate rates of motion. A refined time window is determined based on the estimated rates of motion to monitor the moving object with increased accuracy and/or range compared to the safe time window.

Abstract: According to an aspect of the invention, a method of optimal safe landing area determination for an aircraft includes accessing a probabilistic safe landing area map that includes a plurality of probabilistic indicators of safe landing areas for the aircraft. A processing subsystem that includes one or more processing resources generates a list of candidate safe landing areas based on the probabilistic safe landing area map and one or more constraints. At least two of the candidate safe landing areas are provided to a path planner. The list of candidate safe landing areas is ranked based on results from the path planner indicating an estimated cost to reach each of the candidate safe landing areas. Based on the ranking, an indicator of an optimal safe landing area is output as a desired landing location for the aircraft.

Abstract: A system for registering a target includes a first sensor, a second sensor, and a processor. The first sensor measures a plurality of ranges from a source to a target, and the second sensor obtains a plurality of location measurements of the source. The system further includes a processor configured for determining one or more weighting criteria associated with each one of the plurality of location measurements based on an estimated reliability of each one of the plurality of location measurements. The processor calculates a plurality of target location values based on the plurality of ranges measured by the first sensor and the plurality of locations measured by the second sensor and calculates an estimated target location value based on the plurality of target location values weighted according to the weighting criteria.

Abstract: According to an aspect of the invention, a method of flight initiation proximity warning for an autonomous vehicle is provided. A flight initiation request is detected at a processing system of the autonomous vehicle. A preflight proximity scan is performed for any obstacles within a predetermined distance from the autonomous vehicle based on the flight initiation request. An alert is sent to a control station based on detecting at least one obstacle within the predetermined distance. Flight initiation of the autonomous vehicle is inhibited until an acknowledgement of the alert is received at the processing system of the autonomous vehicle.

Abstract: A method for augmenting a synthetic vision system of a vehicle includes receiving, with a processor, signals indicative of real-time sensor data of a terrain for the vehicle via one or more acquisition devices; creating, with the processor, a terrain mesh of the terrain in response to the receiving of the sensor data; correlating, with the processor, the terrain mesh with preloaded terrain data of the terrain; creating, with the processor, a multispectral image of the terrain in response to the correlating the terrain mesh with the preloaded data; and texturing, with the processor, the terrain mesh for display on a display device.

Abstract: An electronic landing platform state module is configured to generate a state estimation of a platform surface at sea includes a plurality of electronic platform state process modules configured to receive an output from a respective spectral sensor. The plurality of electronic platform state process modules are further configured to output a monitored spectral platform state signal in response to applying a spectral process on a respective output. Each spectral process corresponds to a particular spectral modality of the respective spectral sensor. The electronic landing platform state module further includes an electronic platform state estimator module configured to determine a corrected dynamic state of the platform in response to fusing together the individual monitored spectral platform state signals.

Abstract: A method of cooperative communication link mapping and classification is provided. Location data are received defining a position of a communication node. Signal data of a communication link are monitored at the communication node with respect to a second communication node and characteristics of the signal data are identified. A location stamp of the position is applied to the characteristics of the signal data. The communication link is classified based on the characteristics of the signal data, and a map is populated classifying the communication link at the position indicated by the location stamp.

Abstract: A method of performing a cooperative safe landing area determination includes receiving perception sensor data indicative of conditions at a plurality of potential landing areas. A processing subsystem of a vehicle updates a local safe landing area map based on the perception sensor data. The local safe landing area map defines safe landing area classifications and classification confidences associated with the potential landing areas. One or more remotely-generated safe landing area maps are received from one or more remote data sources. The one or more remotely-generated safe landing area maps correspond to one or more additional potential landing areas and non-landing areas. The local safe landing area map and the remotely-generated safe landing area maps are aggregated to form a fused safe landing area map. The fused safe landing area map is used to make a final safe landing area determination.

Abstract: A method and system for sharing information between independent agents having a processor and memory having instructions stored thereon that, when executed by the processor, cause the system to receive signals indicative of a fault of a sensor system of a first independent agent; transmit signals indicative of a request for sensor information to a second independent agent; receive signals indicative of state information for the second independent agent in response to the receiving of the request for sensor information; and apply the state information to a navigation system of the first independent agent in response to the receiving of the state information.