An aircraft system includes an aircraft, which further includes at least one propeller to provide a flight power for the aircraft; a communication interface configured to communicate with a parachute; at least one storage medium, storing at least one set of instructions for controlling the aircraft system; and at least one processor in communication with the at least one memory. when the aircraft system is in operation, the at least processor executes the at least one set of instruction to: obtain a propeller locking instruction of the aircraft, and perform a corresponding operation based on the propeller locking instruction. The corresponding operation include a first operation. The first operation, corresponds to a scenario where the aircraft is in a flight state, includes: in response to the propeller locking instruction, the aircraft controlling the at least one propeller to stop and locking the at least one propeller, and deploying the parachute by the aircraft.

A parking method is provided, including: obtaining failure indication information when a vehicle is controlled, based on parking control information received from a mobile terminal, to park in or pull out of a parking space, where the failure indication information indicates that at least one of a remote control function of the mobile terminal, a communication network of the vehicle, and a parking-related actuator of the vehicle fails (S401); and controlling, based on the failure indication information, the vehicle to brake (S402). The method may be applied to an autonomous driving vehicle such as an intelligent vehicle or an electric vehicle. When a function fails in a remote parking process, the vehicle can brake in a timely manner, to ensure vehicle safety in the parking process. A parking apparatus, a vehicle, a computer-readable storage medium, and a chip are further disclosed.

A remote support system is for remote support for an automated driving vehicle, and includes one or more processors. The one or more processors are configured to: acquire support request information including content of a remote support request from the automated driving vehicle; acquire a concern message for notifying a concern that possibly arises if a remote supporter provides incorrect remote support to the automated driving vehicle, based on the support request information; and notify the remote supporter of the concern message through a remote support device operated by the remote supporter for the remote support.

A remote operator terminal to be used by a remote operator for a remote operation of a target mobility is provided. The remote operator terminal includes: a plurality of types of operation systems; and a notification device configured to notify the remote operator of information. A first operation system is one of the plurality of types of operation systems. The information indicates a relationship between a maximum operation amount of the first operation system and a current operation amount of the first operation system input by the remote operator, or the information indicates that the current operation amount reaches the maximum operation amount.

A teleoperations system may be used to generate virtual paths of travel for an autonomous vehicle based upon teleoperations system-provided suggestions, and virtual path suggestion constraints, e.g., based upon physical constraints associated with an autonomous vehicle such as minimum turning radius, trailer sweep, and the like, may be used assist in guiding a teleoperations system operator during generation of virtual path suggestions.

A movable platform for taking inventory and/or performing other actions on objects, the movable platform comprising a traction system for allowing the movable platform to circulate through an area, a sensor system for identifying objects in an area based on a characteristic, and for creating information indicative of the identified objects and the position of the identified objects relative to the movable platform and in absolute space coordinates, and a control system, wherein the control system is adapted to receive the information created by the sensor system and to determine a direction of movement or a partial path or a movement target for the movable platform based on the received information and without using a previously created map of the area.

This disclosure presents an assisted driving vehicle system, including autonomous, semi-autonomous, and technology assisted vehicles, that can share sensor data among two or more controllers. A sensor can have one communication channel to a controller, thereby saving cabling and circuitry costs. The data from the sensor can be sent from one controller to another controller to enable redundancy and backup in case of a system failure. Sensor data from more than one sensor can be aggregated at one controller prior to the aggregated sensor data being communicated to another controller thereby saving bandwidth and reducing transmission times. The sharing of sensor data can be enabled through the use of a sensor data distributor, such as a converter, repeater, or a serializer/deserializer set located as part of the controller and communicatively coupled to another such device in another controller using a data interface communication channel.

A movable object according to an embodiment of the present technology includes a body unit, a notification unit, and a notification control unit. The notification unit is provided in the body unit. The notification control unit controls an operation of the notification unit, to thereby notify of information regarding at least one of an orientation of the body unit or a position on the body unit as assistance information for assisting work of a user on the movable object. This enables the user to intuitively recognize which orientation the user should put the body unit in, and the workability in user's work can be improved.

The present application discloses methods and systems for mobility device control by capturing electroencephalogram (EEG) brain wave data to extract steady-state visually evoked potential (SSVEP) signal data and decoding the SSVEP signal data into at least one command for controlling the mobility device. The SSVEP signals are triggered through visual stimuli on a screen of a device, such as a user device, and are decoded through a machine learning pipeline. At least one of cloud, edge or fog principles may be utilized to enhance response time. The use of the machine learning pipeline and at least one of cloud, edge or fog technology provides an improved mobility device control system response time when compared to the current and prior alternatives for mobility device control systems.

A control device according to one aspect of the present disclosure is a device that remotely operates a mobile body. The control device includes an operation unit and a sensor unit. The operation unit that performs reception of an operation for the mobile body. The sensor unit performs detection of a posture of the control device or the mobile body. The control device further includes a generation unit and a communication unit. The generation unit generates posture data of the control device on the basis of a result of the detection performed by the sensor unit. The communication unit transmits, to the mobile body, the posture data generated by the generation unit and operation data obtained by the reception performed by the operation unit.