A cleaning robot includes a top cover, a bottom cover formed below the top cover and configured to move by external force, a fixed body provided in the bottom cover, a first opening formed in an upper portion of the bottom cover and a first sensor connected to the fixed body and externally exposed between the top cover and the bottom cover through the first opening.

An AI apparatus and an operating method are provided, the AI apparatus includes a communication interface to receive 3D sensor data and bumper sensor data from a first cleaner, a processor to generate surrounding situation map data based on the 3D sensor data and the bumper sensor data, and a learning processor to generate learning data by labeling area classification data for representing whether the surrounding situation map data corresponds to the stuck area, and to train a stuck area classification model based on the learning data. The processor transmits the trained stuck area classification model to a second cleaner through the communication interface.

A method includes identifying sensor data associated with corresponding distal ends of one or more axles of an autonomous vehicle (AV). The method further includes determining, based on the sensor data, mass distribution data of the AV. The mass distribution data is associated with a first load proximate a first distal end of a first axle of the AV and a second load proximate a second distal end of the first axle of the AV. The method further includes causing, based on the mass distribution data, performance of a corrective action associated with the AV.

A device and a method for performing control to change a flexible virtual bumper for maintaining a space between a mobile object and an obstacle to be equal to or larger than a predetermined distance are enabled. A data processing unit that executes control to change the flexible virtual bumper for maintaining the space between the mobile object and the obstacle to be equal to or larger than the predetermined distance, and a drive unit that drives the mobile object in such a way that no obstacle enters the flexible virtual bumper are included. The data processing unit executes control to change the flexible virtual bumper at least either in size or shape. For each one of a plurality of travel route candidates for the mobile object, the data processing unit executes a simulation of changing the bumper size in such a way that no obstacle enters the flexible virtual bumper, and selects a safe travel route.

A computer-implemented method of operating an agricultural work machine is provided. The method includes initiating row sensing guidance for the agricultural work machine to guide steering of the agricultural work machine based at least one signal from a row sensor; obtaining contextual information; determining whether a row is present based on the contextual information; and selectively ignoring the at least one signal from the row sensor based on whether a row is present. An agricultural work machine and a control system for an agricultural work machine are also provided.

A robot can include a cart to receive one or more objects; a camera sensor to photograph a periphery of the robot and capture an image of a user of the robot; a handle assembly coupled to the cart; a moving part to move the robot; a force sensor to sense a force applied to the handle assembly; and a controller configured to generate physical characteristics information on physical characteristics of the user of the robot based on the image of the user, and adjust at least one of a moving direction of the robot, a moving speed of the moving part and a value of torque applied to a motor of the moving part, based on the physical characteristics information and a magnitude of the force applied to the handle assembly sensed by the force sensor.

Provided is an autonomous mobile robot, includes a cover, a base and a pressure sensor assembly; the cover includes a top plate and a side plate that are integrally arranged, a connecting portion is formed between the top plate and the side plate, and the connecting portion is at least partially higher than the top plate; the base is arranged below the top plate; and the pressure sensor assembly is arranged in a manner of facing the side plate. The impact of the traditional autonomous mobile robot using a floating bump plate on the positioning accuracy of an optical component may be avoided and the reliability of the autonomous mobile robot during the movement is improved.

Robot localization or mapping can be provided without requiring the expense or complexity of an “at-a-distance” sensor, such as a camera, a LIDAR sensor, or the like. Landmark features can be created or matched using motion sensor data, such as odometry or gyro data or the like, and adjacency sensor data. Despite the relative ambiguity of adjacency-sensor derived landmark features, a particle filter approach can be configured to use such information, instead of requiring “at-a-distance” information from a constant stream of visual images from a camera, such as for robot localization or mapping. Landmark sequence constraints or a Wi-Fi signal strength map can be used together with the particle filter approach.

A robotic vacuum cleaner may include a housing, a displaceable bumper, an emitter/detector pair, and at least one divider. The displaceable bumper may be moveably coupled to the housing and may be configured to be displaced along at least one axis. The emitter/detector pair may have an emitter and a detector, wherein the emitter is configured to emit light through at least a portion of the displaceable bumper. The at least one divider may be disposed between the emitter and the detector of the emitter/detector pair.

A component of an Autonomous Vehicle (AV) system, the component having at least one processor; and a non-transitory computer-readable storage medium including instructions that, when executed by the at least one processor, cause the at least one processor to decode data encoded in a signal, wherein the data identifies a pattern of protrusions embedded in a driving surface, the signal being received from at least one vehicle sensor resulting from a vehicle driving over the pattern of protrusions in the driving surface.