Autonomous carriers or totes that include vacuum units are provided. As the totes move or are moved through a warehouse carrying products, they collect debris. The debris can be analyzed at the tote, and actions can be performed based upon the analysis.

Various embodiments provide systems and/or methods for automated maintenance, delivery, retrieval, and/or communications using drones.

A robot apparatus for establishing a charging connection between a charging device and an energy storage unit of a motor vehicle, having a movement unit, by which the robot apparatus is movable in relation to the charging device and the motor vehicle, having a receptacle device, by which a charging element of the charging device can be received, can be coupled to a coupling element of the energy storage unit and subsequently released, and having a detection unit, by which a position of the coupling element on the motor vehicle is ascertainable, wherein the robot apparatus is connectable by a support device to the motor vehicle, whereby a force is transmittable from the robot apparatus to the motor vehicle.

A parcel delivery system is provided for use in complex having a plurality of tenant units each having a tenant address, wherein the complex further comprising an intake facility, a delivery facility, and parcel storage boxes, and wherein the intake facility comprises a scanning station and a first automated ground delivery vehicle in communication with the scanning station and wherein the delivery facility comprises a second automated ground delivery vehicle configured to travel between the delivery station and tenant units. In accordance with embodiments, a computer system interfaces with the parcel delivery system to notify tenants when they have a parcel and to further notify tenants when delivery of the parcel has been completed.

In various examples, a sequential deep neural network (DNN) may be trained using ground truth data generated by correlating (e.g., by cross-sensor fusion) sensor data with image data representative of a sequences of images. In deployment, the sequential DNN may leverage the sensor correlation to compute various predictions using image data alone. The predictions may include velocities, in world space, of objects in fields of view of an ego-vehicle, current and future locations of the objects in image space, and/or a time-to-collision (TTC) between the objects and the ego-vehicle. These predictions may be used as part of a perception system for understanding and reacting to a current physical environment of the ego-vehicle.

An information processing apparatus includes an accumulation unit that accumulates history information regarding a flight history of an aircraft. A specification unit, based on the history information accumulated by the accumulation unit, specifies a candidate to be an operation assistant who assists an operation planned by an assisted operator. An output unit outputs information regarding the candidate to be the operation assistant specified by the specification unit.

In one embodiment, when an autonomous driving vehicle (ADV) is parked, the ADV can determine, based on criteria, whether to operate in an open-space mode or an on-lane mode. The criteria can include whether the ADV is within a threshold distance and threshold heading relative to a vehicle lane. If the criteria are not satisfied, then the ADV can enter the open-space mode. While in the open-space mode, the ADV can maneuver it is within the threshold distance and the threshold heading relative to the vehicle lane. In response to the criteria being satisfied, the ADV can enter and operate in the on-lane mode for the ADV to resume along the vehicle lane.

Techniques are described for managing redundant steering system for a vehicle. A method includes sending a first control command that instructs a first motor coupled to a steering wheel in a steering system to steer a vehicle, receiving, after sending the first control command, a speed of the vehicle, a yaw rate of the vehicle, and a steering position of the steering wheel, determining, based at least on the speed and the yaw rate, an expected range of steering angles that describes values within which the first motor is expected to steer the vehicle based on the first control command, and upon determining that the steering position of a steering wheel is outside the expected range of steering angles, sending a second control command that instructs a second motor coupled to the steering wheel in the steering system to steer the vehicle.

The application relates to an aircraft, a method, an apparatus and a computer readable storage medium for controlling the aircraft with at least one sensor arranged thereon, the method including detecting a motor state of the aircraft, acquiring at least one sensing data of the at least one sensor, and controlling the aircraft to perform a startup operation or a shutdown operation according to the motor state and the at least one sensing data, so that the aircraft can be autonomously controlled to perform the startup operation or the shutdown operation, and the user experience is improved.

A parking control system for an autonomous vehicle is provided. The parking control system includes a parking control device configured to monitor a location and movement of an autonomous vehicle which enters a parking lot, based on a 3D electronic map, calculate a driving trajectory to a parking space selected by a driver of the autonomous vehicle based on sensor data collected from various sensor in the parking lot and vehicle information received from the autonomous vehicle, and provide information about the calculated driving trajectory to the autonomous vehicle. The autonomous vehicle travels to the parking space based on the driving trajectory received from the parking control device and parks in the parking space.