Abstract: A method including providing a visual cue associated with and in close physical proximity to an object, detecting a pose of the visual cue with a camera coupled to the robot arm, training by guiding the robot arm from a first position to a target position near the object based on external input, recording, by the camera, trajectory data based on the pose of the visual cue during movement of the robot arm from the first position to the target position and storing the trajectory data in memory, receiving an instruction to move the robot arm to the object, providing a sequence of robot arm trajectory instructions relative to the pose of the visual cue based on input from the camera and trajectory data to guide the robot arm to the target position.

Abstract: An image processing system configured to process perceived images of an environment includes a central processing unit (CPU) including a memory storage device having stored thereon a computer model of the environment, at least one sensor configured and disposed to capture a perceived environment including at least one of visual images of the environment and range data to objects in the environment, and a rendering unit (RU) configured and disposed to render the computer model of the environment forming a rendered model of the environment. The image processing system compares the rendered model of the environment to the perceived environment to update the computer model of the environment.

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: An image processing system configured to process perceived images of an environment includes a central processing unit (CPU) including a memory storage device having stored thereon a computer model of the environment, at least one sensor configured and disposed to capture a perceived environment including at least one of visual images of the environment and range data to objects in the environment, and a rendering unit (RU) configured and disposed to render the computer model of the environment forming a rendered model of the environment. The image processing system compares the rendered model of the environment to the perceived environment to update the computer model of the environment.

Abstract: Certain embodiments of the disclosure can include systems and methods for robotic localization and orientation. The systems and methods can include identification of a landmark, such as a landing pad, by a sensor of an unmanned vehicle. The systems and methods can include acquiring coordinates of the landmark; and determining a self-position, by the unmanned vehicle, based on the coordinates of the landmark. The systems and methods can also include determining the position of an object based on the coordinates and the self-position.

Abstract: An image processing system configured to process perceived images of an environment includes a central processing unit (CPU) including a memory storage device having stored thereon a computer model of the environment, at least one sensor configured and disposed to capture a perceived environment including at least one of visual images of the environment and range data to objects in the environment, and a rendering unit (RU) configured and disposed to render the computer model of the environment forming a rendered model of the environment. The image processing system compares the rendered model of the environment to the perceived environment to update the computer model of the environment.

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: 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: An online sensor calibration verification system includes at least one sensor configured to extract a calibration feature included in a field of view of the sensor. The online sensor calibration verification system further includes an electronic calibration verification module configured to determine a static reference feature model, and to verify a calibration of the at least one sensor based on a positional relationship between an extracted calibration feature and the static reference feature model.

Abstract: An image processing system configured to process perceived images of an environment includes a central processing unit (CPU) including a memory storage device having stored thereon a computer model of the environment, at least one sensor configured and disposed to capture a perceived environment including at least one of visual images of the environment and range data to objects in the environment, and a rendering unit (RU) configured and disposed to render the computer model of the environment forming a rendered model of the environment. The image processing system compares the rendered model of the environment to the perceived environment to update the computer model of the environment.

Abstract: An aspect includes a method of kinematic motion planning includes accessing a list of a plurality of nodes defining a plurality of potential kinematic path locations between a starting position and an ending position of a vehicle. A plurality of constraint sets is determined that apply one or more vehicle motion constraints based on a plurality of spatial regions defined between the starting position and the ending position. The constraint sets are applied in determining a plurality of connections between the nodes to form a kinematic motion path based on locations of the nodes relative to the spatial regions. The kinematic motion path is output to a dynamic path planner to complete creation of a motion path plan for the vehicle.

Abstract: An online sensor calibration verification system includes at least one sensor configured to extract a calibration feature included in a field of view of the sensor. The online sensor calibration verification system further includes an electronic calibration verification module configured to determine a static reference feature model, and to verify a calibration of the at least one sensor based on a positional relationship between an extracted calibration feature and the static reference feature model.

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: An aspect includes a method of kinematic motion planning includes accessing a list of a plurality of nodes defining a plurality of potential kinematic path locations between a starting position and an ending position of a vehicle. A plurality of constraint sets is determined that apply one or more vehicle motion constraints based on a plurality of spatial regions defined between the starting position and the ending position. The constraint sets are applied in determining a plurality of connections between the nodes to form a kinematic motion path based on locations of the nodes relative to the spatial regions. The kinematic motion path is output to a dynamic path planner to complete creation of a motion path plan for the vehicle.