An inspection robot incudes a robot body, at least two sensors, a drive module, a stability assist device and an actuator. The at least two sensors are positioned to interrogate an inspection surface and are communicatively coupled to the robot body. The drive module includes at least two wheels that engage the inspection surface. The drive module is coupled to the robot body. The stability assist device is coupled to at least one of the robot body or the drive module. The actuator is coupled to the stability assist device at a first end, and coupled to one of the drive module or the robot body at a second end. The actuator is structured to selectively move the stability assist device between a first position and a second position. The first position includes a stored position. The second position includes a deployed position.

Systems, methods, controllers and algorithms for controlling a vehicle to closely follow another vehicle safely using automatic or partially automatic control are described. The described control schemes are well suited for use in vehicle platooning and/or vehicle convoying applications, including truck platooning and convoying controllers. In one aspect, methods of initiating a platoon between a host vehicle and a platoon partner are described. In another aspect, a number of specific checks are described for determining whether a platoon controller is ready to initiate platoon control of the host vehicle. In another aspect, a platoon controller that includes a state machine that determines the state of the platoon controller is described. In another aspect, methods for generating braking alerts to a driver of a vehicle while the vehicle is being at least semi-automatically controlled by a platoon controller are described.

An autonomous mobile device (AMD) builds up electrostatic charges from moving and generates heat from the operation of internal components. In addition to possible user discomfort, electrostatic discharges may damage sensors and electronics. Electrostatic charges are dissipated from the AMD using an electrostatic dissipation structure and conductive wheels. A conductive path between a chassis ground, the electrostatic dissipation structure, and the conductive wheels improves the dissipation of electrostatic charges. Electrostatic charges are also dissipated from components by mounting the components using conductive materials. Sensors may be affixed to a support structure that is affected by thermal expansion. Thermal expansion may distort precise positioning of sensors, reducing accuracy of sensor data. An elastomeric foam may be used to mount sensors to a support structure, allowing for thermal expansion without distorting the positioning of the sensors.

An industrial truck, configured for driverless, autonomously-acting operation for a load to be transported, includes at least a control system configured to control and to steer the industrial truck, and an evaluation unit configured to generate a signal for stopping the industrial truck. A detector device configured to recognize persons and/or objects located in a route is connected to the control system. The control system is configured to check a protective field and/or a warning field of the detector device, and the protective field and/or the warning field is automatically switchable in dependence on a position of the industrial truck and/or detected obstacles in the route of the industrial truck.

Provided is a process executed by a robot, including: traversing, to a first position, a first distance in a backward direction; after traversing the first distance, rotating in a first rotation; after the first rotation, traversing, to a second position, a second distance in a third direction; after traversing the second distance, rotating 180 degrees in a second rotation such that the field of view of the sensor points in a fourth direction; after the second rotation, traversing, to a third position, a third distance in the fourth direction; after traversing the second distance, rotating 180 degrees in a third rotation such that the field of view of the sensor points in the third direction; and after the third rotation, traversing, to a fourth position, a fourth distance in the third direction.

Systems and methods for initializing a robot to autonomously travel a route are disclosed. In some exemplary implementations, a robot can detect an initialization object and then determine its position relative to that initialization object. The robot can then learn a route by user demonstration, where the robot associates actions along that route with positions relative to the initialization object. The robot can later detect the initialization object again and determine its position relative to that initialization object. The robot can then autonomously navigate the learned route, performing actions associated with positions relative to the initialization object.

A road information detection device includes a curve-starting-position identification part configured to identify the starting position of a transition curve according to a road structure upon detecting an attached structure on a road. It further includes an image information capture part configured to capture an image, an attached-structure detection part configured to detect the identification of an attached structure reflected in the image, and a storage media configured to store the position of an attached structure. The curve-starting-position identification part may identify the starting position based on the detected identification of an attached structure, the stored position of an attached structure, and a distance from the attached structure to the starting position of a transition curve.

A traveling body includes a range sensor and circuitry. The range sensor is disposed on a front face of the traveling body in a traveling direction in which the traveling body travels on a road surface and disposed obliquely downward at an inclination angle relative to the road surface. The circuitry determines presence of a continuous obstacle in a case where measurement results of a plurality of planes scanned by the range sensor include a plurality of feature values indicating unevenness relative to the road surface similar to each other. The circuitry generates an obstacle map of a front region of the traveling body not scanned by the range sensor, based on sequential feature information indicating that a predetermined number of feature values indicating the unevenness are sequentially present and controls the traveling body to travel on the road surface based on the obstacle map.

An localization correction method for a robot, comprising acquiring first position information of the robot in a first coordinate system; acquiring second position information of the robot in a second coordinate system after the robot executes a motion command; establishing a transformation model between the first position information and the second position information based on the first coordinate system and the second coordinate system; calculating a compensation value according to the transformation model; and generating a reset command according to the compensation value, and adjusting the localization of the robot according to the reset command.

A system and method for localization of an autonomous vehicle based on 3D point cloud are disclosed. The system includes a processor and a memory coupled to the processor, the memory tangibly storing thereon executable instructions that, when executed by the processor, cause the processor to: receive an initial position of a vehicle; receive a data file representative of a three-dimensional (3D) point cloud from a LIDAR scanning subsystem of the vehicle; divide the 3D point cloud into a plurality of tiles and compute a plurality of key points for each tile; generate an estimated low frequency 2D position and yaw angle for the vehicle based on a particle filter process and a dynamically downloaded 2D reference map; and generate a position and orientation of the vehicle.