Methods, systems, and apparatus, including computer programs encoded on computer storage media, for unmanned aerial vehicle modular command priority determination and filtering system. One of the methods includes enabling control of the UAV by a first control source that provides modular commands to the UAV, each modular command being a command associated with performance of one or more actions by the UAV. Modular commands from a second control source requesting control of the UAV are received. The second control source is determined to be in control of the UAV based on priority information associated with each control source. Control of the UAV is enabled by the second control source, and modular commands are implemented.

An autonomous vehicle uses a secondary vehicle control system to supplement a primary vehicle control system to perform a controlled stop if an adverse event is detected in the primary vehicle control system. The secondary vehicle control system may use a redundant lateral velocity determined by a different sensor from that used by the primary vehicle control system to determine lateral velocity for use in controlling the autonomous vehicle to perform the controlled stop.

A terminal apparatus includes a camera, a display that displays a display screen including a mobile robot that autonomously travels, and a control circuit. The control circuit acquires a first planned route of the mobile robot, displays, on the display, a screen having the first planned route superimposed on a camera image taken by the camera, detects a contact point on the display on which the screen is displayed, generates a second planned route of the mobile robot that travels through the contact point, and transmits the second planned route to the mobile robot.

Systems and methods of manipulating/controlling robots. In many scenarios, data collected by a sensor (connected to a robot) may not have very high precision (e.g., a regular commercial/inexpensive sensor) or may be subjected to dynamic environmental changes. Thus, the data collected by the sensor may not indicate the parameter captured by the sensor with high accuracy. The present robotic control system is directed at such scenarios. In some embodiments, the disclosed embodiments can be used for computing a sliding velocity limit boundary for a spatial controller. In some embodiments, the disclosed embodiments can be used for teleoperation of a vehicle located in the field of view of a camera.

An amphibious vehicle having a frame that includes a plurality of floatable members. Mounted to the frame is one or more power sources. Also mounted to the frame and connected to the power source are a plurality of propellers with each of the plurality of propellers having a thrust vector configured to be adjusted to provide agitation and propulsion. In addition, mounted to the frame are a plurality of ground engaging devices and one or more pumps.

Systems and methods for path planning with latent state inference and spatial-temporal relationships are provided. A system includes an inference module, a policy module, a graphical representation module, and a planning module. The inference module receives sensor data associated with a plurality of agents. The inference module also maps the sensor data to a latent state distribution to identify latent states of the plurality of agents. The latent states identify agents of the plurality of agents as cooperative or aggressive. The policy module predicts future trajectories of the plurality of agents at a given time based on sensor data and the latent states of the plurality of agents. The graphical representation module generates a graphical representation based on the sensor data and a graphical representation neural network. The planning module generates a motion plan for the ego agent based on the predicted future trajectories and the graphical representation.

In a general aspect, a handheld controller device includes a housing and a trigger assembly. The housing is configured to be held in the hands of a user. The trigger assembly includes a pair of triggers extending outward from a side of the handheld controller device and configured to move along respective trigger paths. A coupling assembly is disposed inside the housing and connected to the pair of triggers. The coupling assembly is configured to transfer motion between the pair of triggers such that, when either of the triggers moves towards the housing along its respective trigger path, the coupling assembly moves the other trigger an equal distance away from the housing along its trigger path. Circuitry in the housing includes one or more sensors and a microcontroller configured to receive sensor signals and, in response, generate aircraft control data (e.g., for a flight simulation or remotely controlled flyable aircraft).

An aerial vehicle comprises one or more sensors to environmental data, a communication system to receive control inputs from a user, two or more actuators, with each actuator coupled to a rotary wing. The aerial vehicle also comprises a controller to determine a mode of the aerial vehicle based on the environmental data and the control inputs, each mode indicating a set of flight characteristics for the aerial vehicle, generate a gain value based on the mode, the gain value, when used to modify power signals transmitted to actuators of the aerial vehicle, causes the aerial vehicle to conform within the indicated flight characteristics of the determined mode, generate an output signal modified by the gain value based on the input signal, and transmit a power signal based on the output signal to each actuator of the aerial vehicle.

Embodiments of the systems and methods disclosed herein describe a data verification of electrical electric components and software systems electronically or mechanically coupled to the electric aircraft by a novel process which starts an electric aircraft and receives physical and software information for each aircraft component or system and determines the status of the health of each of those components or systems. An embodiment may further include a monitoring system configured to measure a plurality of data from each aircraft component and a flight controller communicatively coupled to the monitoring system, wherein the data verification can be performed by the flight controller. Further embodiments may include the flight controller generating an output datum from the assessment produced by the data verification and displaying it to a pilot via an output device.

Technologies for providing augmented reality wayfinding experiences in ridesharing applications are provided. In some examples, a method for providing augmented reality wayfinding experiences can include determining a first location of an autonomous vehicle (AV) relative to a second location of a client device associated with a user that requested a ride from the AV; based on the first location of the AV relative to the second location of the client device, determining a direction from the second location of the client device to the first location of the AV; presenting, at the client device, a feed from a camera sensor associated with the client device, the feed including a local scene captured by the camera sensor; and presenting a virtual content overlay on the feed, the virtual content overlay including an indication of the direction from the second location of the client device to the first location of the AV.