An example carriage is configured for mounting to an unmanned aerial vehicle. The carriage generally includes a housing assembly configured for mounting to the unmanned aerial vehicle, a movable grip mounted to the housing assembly for movement between a capturing position and a releasing position, a latch device, and a driver. The latch device has a latching state and an unlatching state, is configured to retain the movable grip in the capturing position when the latch device is in the latching state, and is configured to permit movement of the movable grip from the capturing position to the releasing position when in the unlatching state. The driver is operable to transition the latch device from the latching state to the unlatching state.

An example carriage is configured for mounting to an unmanned aerial vehicle. The carriage generally includes a housing assembly configured for mounting to the unmanned aerial vehicle, a movable grip mounted to the housing assembly for movement between a capturing position and a releasing position, a latch device, and a driver. The latch device has a latching state and an unlatching state, is configured to retain the movable grip in the capturing position when the latch device is in the latching state, and is configured to permit movement of the movable grip from the capturing position to the releasing position when in the unlatching state. The driver is operable to transition the latch device from the latching state to the unlatching state.

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.

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.

A technique for user interaction with an autonomous unmanned aerial vehicle (UAV) is described. In an example embodiment, perception inputs from one or more sensor devices are processed to build a shared virtual environment that is representative of a physical environment. The sensor devices used to generate perception inputs can include image capture devices onboard an autonomous aerial vehicle that is in flight through the physical environment. The shared virtual environment can provide a continually updated representation of the physical environment which is accessible to multiple network-connected devices, including multiple UAVs and multiple mobile computing devices. The shared virtual environment can be used, for example, to display visual augmentations at network-connected user devices and guide autonomous navigation by the UAV.

A technique for user interaction with an autonomous unmanned aerial vehicle (UAV) is described. In an example embodiment, perception inputs from one or more sensor devices are processed to build a shared virtual environment that is representative of a physical environment. The sensor devices used to generate perception inputs can include image capture devices onboard an autonomous aerial vehicle that is in flight through the physical environment. The shared virtual environment can provide a continually updated representation of the physical environment which is accessible to multiple network-connected devices, including multiple UAVs and multiple mobile computing devices. The shared virtual environment can be used, for example, to display visual augmentations at network-connected user devices and guide autonomous navigation by the UAV.

Embodiments of the present invention are an unmanned aerial vehicle (UAV) severe low-power protection method and a UAV. The method includes: first acquiring ground environment information when the UAV is in a severe low-power protection state, and then obtaining landing safety judgment information according to the ground environment information, and further controlling a flight state of the UAV according to the landing safety judgment information to realize a safe landing of the UAV The foregoing method reduces the probability of explosion of the UAV, avoids injury accidents, and improves flight safety when the UAV is in a severe low-power state.

Embodiments of the present invention are an unmanned aerial vehicle (UAV) severe low-power protection method and a UAV. The method includes: first acquiring ground environment information when the UAV is in a severe low-power protection state, and then obtaining landing safety judgment information according to the ground environment information, and further controlling a flight state of the UAV according to the landing safety judgment information to realize a safe landing of the UAV The foregoing method reduces the probability of explosion of the UAV, avoids injury accidents, and improves flight safety when the UAV is in a severe low-power state.

Described herein are systems for roof scan using an unmanned aerial vehicle. For example, some methods include capturing, using an unmanned aerial vehicle, an overview image of a roof of a building from above the roof; presenting a suggested bounding polygon overlaid on the overview image to a user; determining a bounding polygon based on the suggested bounding polygon and user edits; based on the bounding polygon, determining a flight path including a sequence of poses of the unmanned aerial vehicle with respective fields of view at a fixed height that collectively cover the bounding polygon; fly the unmanned aerial vehicle to a sequence of scan poses with horizontal positions matching respective poses of the flight path and vertical positions determined to maintain a consistent distance above the roof; and scanning the roof from the sequence of scan poses to generate a three-dimensional map of the roof.

Described herein are systems for roof scan using an unmanned aerial vehicle. For example, some methods include capturing, using an unmanned aerial vehicle, an overview image of a roof of a building from above the roof; presenting a suggested bounding polygon overlaid on the overview image to a user; determining a bounding polygon based on the suggested bounding polygon and user edits; based on the bounding polygon, determining a flight path including a sequence of poses of the unmanned aerial vehicle with respective fields of view at a fixed height that collectively cover the bounding polygon; fly the unmanned aerial vehicle to a sequence of scan poses with horizontal positions matching respective poses of the flight path and vertical positions determined to maintain a consistent distance above the roof; and scanning the roof from the sequence of scan poses to generate a three-dimensional map of the roof.