An automated storage and retrieval system including a storage structure with storage racks having a seating surface configured to support case units where a position of each case unit is non-deterministic for each storage location on the storage racks, each case unit has a predetermined storage position and a controller is configured to determine the predetermined storage position, a picking aisle configured to provide access to the case units within the storage structure, and a seismic disturbance restorative system including seismic disturbance motions sensors disposed on the storage racks, a seismic disturbance control module in communication with the seismic disturbance sensors and configured to identify a seismic disturbance, and an automated case mapper configured to traverse the picking aisle, the automated case mapper being in communication with and initialized by the seismic disturbance control module to identify a seated position of at least one case unit within the storage structure.

Method and system for navigating an autonomous vehicle in an open-pit site. The method involves acquiring multiple observations and odometry data from various poses while driving, accessing a topological map of the site with intersections and segments; accessing an observational map of the site with past observations including surroundings information linked to an intersection or segment, processing past observations, acquired observations, and odometry data, applying particle filtering techniques and Gaussian Processes to model observations from discrete poses as a continuous variable and estimate the current pose, statistically predicting the next pose based on the current direction of movement; commanding the autonomous vehicle via actuators controlled by the processor unit, based on detecting whether the vehicle is in a segment or intersection, and issuing either a moving-forward instruction to traverse the segment or a steering instruction to take a subsequent segment.

An automated storage and retrieval system including a storage structure with storage racks having a seating surface configured to support case units where a position of each case unit is non-deterministic for each storage location on the storage racks, each case unit has a predetermined storage position and a controller is configured to determine the predetermined storage position, a picking aisle configured to provide access to the case units within the storage structure, and a seismic disturbance restorative system including seismic disturbance motions sensors disposed on the storage racks, a seismic disturbance control module in communication with the seismic disturbance sensors and configured to identify a seismic disturbance, and an automated case mapper configured to traverse the picking aisle, the automated case mapper being in communication with and initialized by the seismic disturbance control module to identify a seated position of at least one case unit within the storage structure.

An autonomous transport robot for transporting a payload, autonomous transport robot including, frame with integral payload support that has a payload seat surface defining a payload datum position that determines predetermined payload position relative to autonomous transport robot, transfer arm connected to the frame and configured for autonomous transfer of payload to and from the frame, one caster wheel mounted to frame, drive section with a pair of traction drive wheels astride the drive section, drive section being connected to the frame, wherein the one caster wheel and one traction drive wheel of the pair of traction drive wheels roll, on a rolling surface effecting autonomous transport robot traversal over the rolling surface, each having a fully independent suspension, and are disposed on the frame astride the integral payload support so that the payload seat surface at the payload datum position is disposed at minimum distance above the rolling surface.

Disclosed is a test device and method for remote control parking, falling within the technical field of testing. The method provided by the present disclosure includes the following steps: responding to a remote control parking instruction sent by a portable terminal, and acquiring position and pose data of a vehicle in real-time; injecting function loss conditions; determining a stopping position of the vehicle according to the position and pose data if an alarm signal or a parking success signal sent by an in-vehicle infotainment system is received; and determining a test result of remote control parking according to the stopping position of the vehicle and the function loss conditions. The present disclosure is used to test the response of a vehicle parking under the function loss condition.

A method of operating a vehicle convoy that includes a leader vehicle generating and transmitting a control command for and to at least one follower vehicle that includes a current timestamp, a drive action to be performed by the at least one follower vehicle and a spatial and/or temporal condition to be fulfilled prior to carrying out the drive action, the drive action including at least one of steering the at least one follower vehicle, changing the speed of the at least one follower vehicle and setting the speed of the at least one follower vehicle, the at least one follower vehicle receiving the control command from the leader vehicle and carrying out the drive action included in the received control command when the spatial and/or temporal condition included in the received control command is fulfilled.

An apparatus for estimating a position of a target may include a particle generator to generate a plurality of particles on a map, a particle selector to calculate position accuracy of each of the plurality of particles, based on data sensed related to a position of a target, and select, as a reference particle, at least one of the plurality of particles, based on the position accuracy, and a position determining device to determine the position of the target, based on the reference particle.

Aspects of the disclosure provide a method of providing a destination to an autonomous vehicle in order to enable the autonomous vehicle to collect data according to a targeted driving goal. For instance, a current location of an autonomous vehicle may be received. A set of destinations may be selected from a plurality of predetermined destinations. A route may be determined for each destination. A relevance score may be determined for each destination based on the determined routes and the targeted driving goal. Each destination may be assigned to one of a set of two or more buckets based on the relevance scores. A destination of the set may be selected based on a predetermined sampling probability. The selected destination is sent to the autonomous vehicle in order to cause the autonomous vehicle to travel to the selected destination in an autonomous driving mode.

A method for controlling movement of an autonomous mobile device is provided. The method includes controlling the autonomous mobile device to move along an edge of a first obstacle. The method also includes determining detection of a second obstacle in a moving direction, the first obstacle and the second obstacle forming a corner. The method also includes determining a first location of the autonomous mobile device. The method also includes determining a projected location adjacent the second obstacle. The method also includes determining a curved path connecting the first location and the projected location. The method also includes controlling the autonomous mobile device to move from the first location to the projected location along the curved path.

Systems and methods are described for instructing performance of a localization and an action by a mobile robot based on composite data. A system may obtain satellite-based position data and one or more of odometry data or point cloud data. The system may generate composite data by merging the satellite-based position data and the one or more of the odometry data or the point cloud data. The system may instruct performance of a localization by the mobile robot based on the composite data. Based on the localization by the mobile robot, the system may identify an action and instruct performance of the action by a mobile robot.