A remote support system performs a remote support of a moving body. The remote support system includes processing circuitry. The processing circuitry is configured to acquire, via communication, a first video shot with a first infrastructure camera installed in a target area in which the moving body moves. The processing circuitry is configured to present the first video to a remote supporter to perform the remote support for the moving body. When an abnormality occurs in the first video, the processing circuitry is configured to execute an abnormality handling process to resolve the abnormality in the first video or to present a substitute video to the remote supporter instead of the first video.

A remote support system performs a remote support of a moving body. The remote support system includes processing circuitry. The processing circuitry is configured to acquire, via communication, a first video shot with a first infrastructure camera installed in a target area in which the moving body moves. The processing circuitry is configured to present the first video to a remote supporter to perform the remote support for the moving body. When an abnormality occurs in the first video, the processing circuitry is configured to execute an abnormality handling process to resolve the abnormality in the first video or to present a substitute video to the remote supporter instead of the first video.

Various aspects of methods, systems, and use cases include techniques for robotic relocalization. A robot may be configured to perform relocalization using operations to determine a cause of a loss of pose; use a nearest neighbor process to select a set of milestones from a roadmap when the cause of the loss of pose is due to a malfunction, or use a ranking process to select the set of milestones from the roadmap when the cause of the loss of pose is not due to the malfunction, the roadmap including a plurality of milestones; generate particle clouds around each milestone in the set of milestones; and perform localization on each milestone in the set of milestones to attempt to relocalize the robot.

Various aspects of methods, systems, and use cases include techniques for robotic relocalization. A robot may be configured to perform relocalization using operations to determine a cause of a loss of pose; use a nearest neighbor process to select a set of milestones from a roadmap when the cause of the loss of pose is due to a malfunction, or use a ranking process to select the set of milestones from the roadmap when the cause of the loss of pose is not due to the malfunction, the roadmap including a plurality of milestones; generate particle clouds around each milestone in the set of milestones; and perform localization on each milestone in the set of milestones to attempt to relocalize the robot.

When a remotely controlled work machine loses a wireless connection on a work site, operation of the work machine should be terminated for safety purposes. However, if the work machine is moving when the wireless connection is lost, the work machine will continue moving for some time due to inertia. Accordingly, embodiments predict the signal quality of a wireless connection as a work machine approaches a new geographical location. When the predicted signal quality is low, the work machine may be proactively derated before it enters the geographical location. After entering the geographical location, if the actual signal quality is significantly better than the predicted signal quality, the work machine may be rerated. The predicted signal qualities may be determined based on a signal map that is independently maintained and updated by each work machine, so as to evolve over time with the work site and the work machine.

When a remotely controlled work machine loses a wireless connection on a work site, operation of the work machine should be terminated for safety purposes. However, if the work machine is moving when the wireless connection is lost, the work machine will continue moving for some time due to inertia. Accordingly, embodiments predict the signal quality of a wireless connection as a work machine approaches a new geographical location. When the predicted signal quality is low, the work machine may be proactively derated before it enters the geographical location. After entering the geographical location, if the actual signal quality is significantly better than the predicted signal quality, the work machine may be rerated. The predicted signal qualities may be determined based on a signal map that is independently maintained and updated by each work machine, so as to evolve over time with the work site and the work machine.

A control device controls a flight of an eVTOL including a rotary wing which is driven by a driving device to generate a rotational lift, a fixed wing which generates a gliding lift, and a lift adjustment mechanism which adjusts the gliding lift. The control device includes a rotary wing control unit which adjusts the rotational lift by controlling driving of the rotary wing, and a fixed wing control unit which adjusts the gliding lift by controlling driving of the lift adjustment mechanism. When an abnormality of the driving device is predicted or detected in a flight time of an electric flight vehicle, the rotary wing control unit and the fixed wing control unit perform lift adjustment control such that the rotary wing control unit reduces the rotational lift and the fixed wing control unit increases the gliding lift.

A control device controls a flight of an eVTOL including a rotary wing which is driven by a driving device to generate a rotational lift, a fixed wing which generates a gliding lift, and a lift adjustment mechanism which adjusts the gliding lift. The control device includes a rotary wing control unit which adjusts the rotational lift by controlling driving of the rotary wing, and a fixed wing control unit which adjusts the gliding lift by controlling driving of the lift adjustment mechanism. When an abnormality of the driving device is predicted or detected in a flight time of an electric flight vehicle, the rotary wing control unit and the fixed wing control unit perform lift adjustment control such that the rotary wing control unit reduces the rotational lift and the fixed wing control unit increases the gliding lift.

An anomaly detection device includes processing circuitry and a memory. The memory stores map data and association data. The map data defines a map. The map receives, as input data, manipulation value data and the image data of the vehicle, thereby outputting, as output data, a state ID corresponding to an anomaly state related to the vehicle. The association data associates an anomaly state related to the vehicle with the state ID. The processing circuitry is configured to acquire the manipulation value data, acquire the image data from a camera mounted in the vehicle, input, as the input data, the manipulation value data and the image data, to the map, thereby acquiring, as the output data, the state ID from the map, and identify the anomaly state related to the vehicle based on the state ID acquired from the map and the association data.

The present disclosure provides vehicle collision avoidance system (CAS) that includes a first CAS module for a robotic vehicle that includes an interface to a first network; a hard stop interface communicatively coupled to the robotic vehicle; one or more computer processors; one or more computer readable storage media; and program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the stored program instructions including instructions to: determine a relative position of a second CAS module based on information from the first network; responsive to determining that the second CAS module is within a first distance from the first CAS module, issue an alert; and responsive to determining that the second CAS module is within a second distance from the first CAS module, transmit a hard stop signal to the robotic vehicle.