Disclosed are a method for dividing a robot area based on boundaries, a chip and a robot. The method includes: setting, when the robot travels along the boundaries in a preset boundary direction in an indoor working area, a reference division boundary line according to data scanned by a laser sensor of the robot in real time; and identifying, after the robot finishes traveling along the boundaries in the preset boundary direction, a door at a position of the reference division boundary line according to image characteristic information of the position of the reference division boundary line acquired by a camera of the robot, and marking the reference division boundary line on a laser map, so as to divide the indoor working area into different room subareas by means of the door.

Disclosed are a method for determining a working start point in a movement limit frame of a robot (P) and a method for controlling movement of a robot. The method for determining the working start point includes: setting a limit frame on a map constructed by the robot (P); and selecting, according to an overlap relation between a map area framed by the limit frame and the map constructed by the robot (P), an overlap area for developing a working start point of the robot (P), and determining a center point (O1, O2, O3, O4, O5, O6, O7, O8) of the overlap area which is selected as the working start point in the limit frame of the robot (P); and the limit frame encloses an area for limiting a working range of the robot (P).

An automated vehicle comprising: a control unit configured to control movement of the automated vehicle to a location adjacent an estimated location of a drill hole; a scanning portion including one or more scanning devices configured to scan an area of terrain in the vicinity of the estimated location of the drill hole in order to determine an actual location of the drill hole, and to generate a point cloud representing at least a portion of the interior of the drill hole; at least one arm associated with the scanning portion, the at least one arm configured to move the scanning portion between a home position and one or more scanning positions; and an end effector associated with the at least one arm, the end effector being configured to perform one or more operations;
wherein, upon generating the point cloud, the at least one arm is configured, based on the point cloud, to position the end effector in substantial alignment with the drill hole so that the end effector can perform the one or more operations.

A location estimation system includes at least four directional sensors that each acquire data used to estimate a location of a mobile object; a sensor assignment section that assigns one of the at least four sensors as a first sensor, and assigns, as a second sensor, one of the at least four sensors that is adjacent to the first sensor and situated on one of sides of the first sensor; an environment map generator that generates an environment map on the basis of first sensor data that is data acquired by the first sensor and on the basis of second sensor data that is data acquired by the second sensor; a first location estimator that estimates the location in the environment map on the basis of the first sensor data to generate a first sensor estimated location; a second location estimator that estimates the location in the environment map on the basis of the second sensor data to generate a second sensor estimated location; and a location integration section that integrates the first sensor estimated location and the second sensor estimated location to estimate the location of the mobile object in the environment map.

A map in a cloud service stores physical objects previously detected by other vehicles that have previously traveled over the same road that a current vehicle is presently traveling on. New data received by the cloud service from the current vehicle regarding new objects that are being encountered by the current vehicle can be compared to the previous object data stored in the map. Based on this comparison, an operating status of the current vehicle is determined. In response to determining the status, an action such as terminating an autonomous navigation mode of the current vehicle is performed.

The invention relates to a medical robot (10) comprising a motorized mobile base (13), spatial-location sensors (17) secured to the mobile base, and a control unit (16) that stores in memory an intervention plan comprising at least one action to be performed on the anatomy of interest of a patient (30). The control unit is configured to: detect, from information coming from the spatial-location sensors (17), a position of the anatomy of interest of the patient with respect to the medical robot, identify, from the position of the anatomy of interest of the patient and from the intervention plan, at least one favourable position of the mobile base of the medical robot for which position the medical robot is capable of performing the action or actions from the intervention plan, move the mobile base of the medical robot into an optimal position selected from among the favourable position or positions identified.

A system and method are described that provide for queueing robot operations in a warehouse environment based on workflow optimization instructions. In one example of the system/method of the present invention, a control system causes certain robots to queue proximate to one another to permit resources to be obtained, transported, deposited, etc. without the robots crashing into one another (or into other objects), or forming traffic jams. A robot may remain at an assigned queue position at least until another position assigned to the robot becomes available.

A system and method are described that provide for mapping features of a warehouse environment having improved workflow. In one example of the system/method of the present invention, a mapping robot is navigated through a warehouse environment, and sensors of the mapping robot collect geospatial data as part of a mapping mode. A Frontend N block of a map framework may be responsible for reading and processing the geospatial data from the sensors of the mapping robot, as well as various other functions. The data may be stored in a keyframe object at a keyframe database. A Backend block of the map framework may be useful for detecting loop constraints, building submaps, optimizing a pose graph using keyframe data from one or more trajectory blocks, and/or various other functions.

An electronic apparatus for controlling a robot cleaner and an operation method thereof. The electronic apparatus that obtains position information, by using a wireless communication interface, based on at least one of a position of a position tracking tag device, a position of at least one home appliance located around the robot cleaner, and a relative position between the robot cleaner and the electronic apparatus, determines a target cleaning region based on the obtained position information, and transmits information about the determined target cleaning region to the robot cleaner.

Disclosed is a load handling controller and a method for localizing a load handling vehicle and a load target. A spatial map describing a surrounding of the load handling vehicle is obtained. First sensor signals are received from a first sensor system for generating point clouds of the surrounding of the load handling vehicle and second sensor signals are received from a second sensor system for generating images of the surrounding of the load handling vehicle. The second sensor signals are synchronized in time with the first sensor signals. The load handling vehicle and the load target are localized in the spatial map based on the first sensor signals and the second sensor signals.