A vehicle, Lidar system and method of detecting an object is disclosed. The Lidar system includes a photonic chip, and a laser integrated into the photonic chip. The laser has a front facet located at a first aperture of the photonic chip to direct a transmitted light beam into free space. A reflected light beam that is a reflection of the transmitted light beam is received at the photonic chip and a parameter of the object is determined from a comparison of the transmitted light beam and the reflected light beam. A navigation system operates the vehicle with respect to the object based on a parameter of the object.

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 vehicle control apparatus comprises a first detection unit configured to have a first detection range, a second detection unit configured to have a second detection range which at least partially overlaps the first detection range, and a vehicle control unit configured to be capable of performing vehicle control based on a first control state and vehicle control based on a second control state which has a high vehicle control automation rate or a reduced degree of vehicle operation participation requested to a driver compared to the first control state. The vehicle control unit performs control to shift from the first control state to the second control state based on a condition that a match degree between pieces of preceding object information of a vehicle detected by the first detection unit and the second detection unit.

A system and method for improving a position accuracy of a mobile robot is disclosed. A retroreflective device is mounted to the mobile robot and used by an absolute positioning device to use a laser beam to track a position of the mobile robot. The mobile robot receives position measurements. Various optimizations may be performed to support operating the mobile robot over a 360 degree range of azimuthal headings.

A control device includes a storage device which has stored a program, and a hardware processor, in which the hardware processor executes the program stored in the storage device, thereby acquiring a peripheral image of the mobile object, which is an image captured by a fisheye camera mounted on a mobile object, calculating an instruction regarding future traveling of the mobile object as a base trajectory in an orthogonal coordinate system, coordinate-converting the acquired base trajectory in the orthogonal coordinate system into a base trajectory in a fisheye camera coordinate system, calculating a risk of the base trajectory in the fisheye camera coordinate system on the basis of the peripheral image, and the base trajectory in the fisheye camera coordinate system, and calculating a traveling trajectory by modifying the base trajectory in the orthogonal coordinate system on the basis of the risk of the base trajectory in the fisheye camera coordinate system.

A method includes: selecting first control parameters for a perimeter intrusion detector of a mobile automation apparatus; controlling the perimeter intrusion detector according to the first control parameters, to monitor a first perimeter surrounding the mobile automation apparatus; determining that navigational data of the mobile automation apparatus defines a maneuver satisfying perimeter modification criteria; in response to determining that a likelihood of intrusion of the first perimeter associated with the maneuver exceeds a threshold, selecting second control parameters for the perimeter intrusion detector; modifying the first perimeter to a second perimeter according to the second control parameters; and controlling the perimeter intrusion detector to monitor the second perimeter.

An embodiment of the present invention provides an artificial intelligence (AI) robot for determining a cleaning route using sensor data, comprising: a sensor unit including at least one of an image sensor, a depth sensor or a shock sensor; a cleaning unit including at least one of a suction unit or a mopping unit; a driving unit configured to drive the AI robot; and a processor configured to: acquire the sensor data from the sensor unit, determine a complex area using the acquired sensor data, create a virtual wall for blocking an entry into the determined complex area, determine the cleaning route in consideration of the created virtual wall, and control the cleaning unit and the driving unit based on the determined cleaning route.

An automatic wall climbing type radar photoelectric robot system for damages of a bridge and tunnel structure, mainly including a control terminal, a wall climbing robot and a server. The wall climbing robot generates a reverse thrust by rotor systems, moves flexibly against the surface of a rough bridge and tunnel structure by adopting an omnidirectional wheel technology, and during inspection by the wall climbing robot, bridges and tunnels do not need to be closed, and the traffic is not affected. Bridges and tunnels can divide into different working regions only by arranging a plurality of UWB base stations, charging and data receiving devices on the bridge and tunnel structure by means of UWB localization, laser SLAM and IMU navigation technologies, a plurality of wall climbing robots supported to work at the same time, automatic path planning and automatic obstacle avoidance realized, and unattended regular automatic patrolling can be realized.

A method for controlling a sensor assembly cleaning apparatus includes receiving sensor data from various vehicle sensors, determining a level of obscurement of the transparent surface, and determining whether the level of obscurement exceeds a threshold level. If the transparent surface is obscured beyond the threshold level, a control signal may be sent to the apparatus to initiate the ejection of pressurized air onto the transparent surface. Optionally, the method may further evaluate other parameters such as the vehicle velocity in relation to a threshold vehicle velocity prior to sending the control signal to ensure that the cleaning operation using pressurized air would not be superfluous in light of the vehicle velocity. In addition, a method for selectively activating the sensor assembly cleaning apparatus includes determining an activation schedule for the apparatus based on an arrangement of transparent surfaces and controlling the apparatus to operate based on the activation schedule.

Technologies disclosed relate to a remote intervention system for the operation of a vehicle, which can be an autonomous vehicle, a vehicle that includes driver assist features, a vehicle used for ride sharing services or the like. The system includes a vehicle sending a request for remote intervention to a remote operator when the operation of the vehicle is suspended. The request for remote intervention can include a request for object identification or a request for decision confirmation. The vehicle can update vehicle operation based in part on vehicle-based sensor data and a response to the remote intervention request from the remote operator. The remote operator can be a human operator or an AI operator.