A vehicle body transport system includes an unmanned carrier carrying and transporting a vehicle body between work stations; and an imaging device including an imaging part imaging a traveling route of the unmanned carrier and the surroundings of the traveling route from above, an analysis part analyzing an image captured by the imaging part, and a transmission part transmitting a signal to the unmanned carrier. When a moving object other than the unmanned carrier carrying the vehicle body is present in the image, the analysis part predicts whether a movement trajectory that the vehicle body passes after a predetermined time intersects a movement position where the moving object is located after the predetermined time. When predicting that the movement trajectory and the movement position intersect after the predetermined time, the transmission part transmits an emergency operation signal to the unmanned carrier before the predetermined time elapses.

A method for performing an autonomous inspection. The method comprises traversing, by an autonomous sensor apparatus, a path through a site having three-dimensional objects located therein. The site includes three-dimensional objects located therein. The method comprises obtaining, by a plurality of sensors on-board the autonomous sensor apparatus, one or more data sets throughout the path. Each of the one or more data sets are associated with an attribute of one or more three-dimensional objects. The method comprises generating, by the first, second, or third processor, a working model from a collocated data set; and comparing, by the first, second, or third processor, the working model with one or more pre-existing models; to determine the presence and/or absence of anomalies. The presence and/or absence of anomalies are communicated as human-readable instructions.

A physical space includes obstacles with different characteristics. Different sensors may detect some obstacles well, while other obstacles are poorly detected. An autonomous mobile device (AMD) uses data from various sensors to determine information about the physical space that is expressed in layers. Each layer represents specified areas within at least a portion of the physical space, with each area having a value representative of whether an obstacle is present. Some layers may represent specific volumes, or height ranges. For example, different layers may represent a low height, a medium height, and a high height. Aggregated data may be determined using the values from multiple layers. The aggregated data may be calculated using an aggregation profile to specify a relative weighting for the values in a particular layer. The aggregated data may then be processed to determine maps, such as a navigation map for autonomous movement, floorplan, and so forth.

Systems and methods for providing opportunities for interactions and communication between vehicles and passengers. In particular, a vehicle socialization platform is provided for facilitating a wide range of social and utilitarian exchanges between vehicles and their occupants, thus providing a community of interconnected vehicles. Vehicle interactions can include passive communication, including vehicles from a particular fleet acknowledging other fleet vehicles without intervention from a passenger or user. Vehicle interactions can include active communication, in which passengers are engaged with and have some control over vehicle communications through dedicated experiences provided in a ridehail application or on an in-vehicle tablet. In particular, some experiences can become dynamically available based on the fleet vehicle's proximity to another fleet vehicle. The vehicle socialization platform is a smart socialization platform that enables two-way communication between vehicles and passengers, facilitating a wide range of social and utilitarian exchanges between vehicles and vehicle occupants.

An information processing system controls an autonomous traveling body capable of autonomously traveling on a learned route. The information processing system includes a route information storage unit to store suspension point information indicating a suspension point at which the autonomous traveling body has suspended autonomous traveling on a particular learned route, and an acquisition unit to acquire current position information indicating a current position of the autonomous traveling body according to an instruction to resume the autonomous traveling, and controls the autonomous traveling body to return to the particular route, based on at least the current position information and the suspension point information.

Provided are an autonomous movable body control system, an autonomous movable body, and a control device, each capable of stopping the autonomous movable body safely. The autonomous movable body control system according to the present disclosure includes a plurality of autonomous movable bodies, and a control device that transmits a control signal for controlling at least one of the plurality of autonomous movable bodies as a control target to each of the plurality of autonomous movable bodies. In the system, among the plurality of autonomous movable bodies, an autonomous movable body other than the control target determines whether an own movable body of the autonomous movable body is located within a stoppable region, and stops based on the result of the determination.

The present disclosure provides a parameter selection device for a work machine that enables the work machine to efficiently travel at a work site where a travel route or a slope changes from moment to moment. The parameter selection device includes a parameter selection section. The parameter selection section calculates an average loaded travel distance per cycle, a travel ratio for each slope in loaded travel, and a virtual travel distance for each slope per cycle of the work machine (processing P1-P3). Further, the parameter selection section calculates a predicted fuel consumption amount for each slope per cycle, a travel time for each slope per cycle, a predicted fuel consumption amount per unit load weight, and a predicted production amount per cycle (processing P4-P8). Then, the parameter selection section selects a recommended parameter set, based on the predicted fuel consumption amount and the predicted production amount per cycle for each parameter set (processing P9).

A device includes: an appearance information acquisition unit configured to acquire measured appearance information on an appearance of a mobile body; a movement information acquisition unit configured to acquire movement information on movement of the mobile body; a determination unit configured to determine whether a deficiency has occurred in the measured appearance information; a complement unit configured to, in a case where the determination unit determines that the deficiency has occurred, use the movement information to complement the deficiency in the measured appearance information; and an estimation unit configured to estimate at least one of a position and an orientation of the mobile body by comparing reference appearance information on the appearance of the mobile body with the measured appearance information, and, in a case where the determination unit determines that the deficiency has occurred, compare the complemented measured appearance information with the reference appearance information.

Examples provide a system and method for controlling a vehicle or a fleet of vehicles. The system includes a set of vehicle sensors configured to measure a speed of the vehicle and a motor torque. The system also includes an electronic processor configured to determine a modeled rack force of the vehicle, determine a normal force factor of the vehicle, determine a vehicle speed factor of the vehicle, determine an adjusted rack force based on a product of the modeled rack force, the normal force factor, and the vehicle speed factor, determine a lateral slip angle of the vehicle, and determine a coefficient of friction estimation based on the adjusted rack force and the lateral slip angle. The electronic processor is further configured to control the vehicle based on the coefficient of friction estimation.

A work vehicle that performs auto-steer driving in forward travel and backward travel includes a position sensor to output chronological position data of the work vehicle, a controller configured or programmed to, in an automatic steering mode, perform steering control for the work vehicle based on the chronological position data and a target path that is previously set, and a toggling switch to switch between forward travel and backward travel of the work vehicle. In the automatic steering mode, when a moving speed of the work vehicle is lower than a first speed, the controller is configured or programmed to determine a traveling direction of the work vehicle based on the chronological position data and a state of the toggling switch.