An autonomous traveling apparatus includes a traveling body. The traveling body includes a first wheel portion and a second wheel portion each provided along a traveling direction of the autonomous traveling apparatus in the traveling body with a predetermined space being interposed between the first wheel portion and the second wheel portion. The second wheel portion has a pair of wheels. The autonomous traveling apparatus further includes a laser sensor. The laser sensor is configured to detect an object around the laser sensor, and is provided on the traveling body to avoid a portion above each of the pair of wheels such that a scanning plane is lower than a maximum reach point of a range of an upward/downward movement of each of the pair of wheels, the scanning plane being a range in which the laser light passes while rotating the laser light.

An apparatus for localizing a robot having robustness to a dynamic environment includes a map building unit which builds a map based on SLAM; a localizing unit which acquires first feature from sensor data acquired by a sensor mounted in a robot and localizes the robot using the first feature acquired from the sensor data based on the map built by the map building unit; and a map updating unit which reduces an error caused by the movement of the robot by correcting the first feature using an estimated position of the robot with regard to a feature obtained from a static object, among the first features acquired by the localizing unit.

The apparatus for detecting and removing a dynamic obstacle of a robot and the operating method thereof according to a predetermined exemplary embodiment detect and remove the dynamic obstacle while simultaneously performing the mapping and the localizing using the simultaneous localization and mapping (SLAM) technique to efficiently detect and remove a dynamic obstacle even in a situation in which a dynamic change of surrounding environment is severe and an environment to be localized is large.

An apparatus and a method for editing 3D SLAM data according to an exemplary embodiment of the present disclosure directly edits a key frame or an edge of simultaneous localization and mapping (SLAM) data by the user's manipulation, optimizes a pose graph of the 3D SLAM data based on the key frame and the edge edited by the user's manipulation, and generates a 2D grid map corresponding to the 3D SLAM data based on the updated 3D SLAM data to improve the convenience of the user for editing the 3D SLAM data.

Provided is a robot device and a method of controlling same. The robot device includes: at least one memory storing at least one instruction; a sensor configured to detect an environment of the robot device and output detection data; and at least one processor configured to execute the at least one instruction to: acquire a map of a space where the robot device is positioned based on the detection data received from the sensor, and a reliability value of each of a plurality of areas of the map, store the map and the reliability value of each of the plurality of areas in the at least one memory, identify at least one area having a reliability value greater than or equal to a critical value, based on the reliability value of each of the plurality of areas, and identify a movement path of the robot device in the space, based on the at least one area.

A method creates an environment map of a surrounding region for the operation of a mobile, self-moving appliance, in particular a floor cleaning appliance such as a vacuum cleaning and/or sweeping and/or mopping robot. The method includes: detecting the region around the appliance with at least one first sensor, to create a first horizontal plane of the environment map; detecting the region around the appliance with at least one second sensor, to create a second horizontal plane of the environment map, which is different from the first horizontal plane; and planning a movement path of the appliance based on the first and second planes of the environment map, in order in particular to achieve the maximum floor processing possible in the surrounding region.

A conveyance system according to the present disclosure includes a conveyance vehicle configured to travel along a guide line laid on a traveling road. The conveyance vehicle includes: a guide line detection unit configured to detect the guide line; an object position detection unit configured to detect information on a position of an object around the conveyance vehicle; and a stop position determination unit configured to determine a stop position of the conveyance vehicle based on a result of detection by the object position detection unit.

An autonomous mobile vehicle for loading and unloading goods in an environmental field, and a guidance and obstacle avoidance method are provided. The autonomous mobile vehicle includes a vehicle body, a first Lidar module, and a second Lidar module. The vehicle body is configured to carry goods, the first Lidar module is fixed on the vehicle body and the second Lidar module is selectively assembled on and disassembled from the vehicle body. When the second Lidar module is assembled on the vehicle body, the autonomous mobile vehicle uses the second Lidar module to establish a map of the environmental field. When the second Lidar module is disassembled from the vehicle body, the autonomous mobile vehicle is guided by using the first Lidar module according to the map, so as to perform an obstacle avoidance on a moving path of the autonomous mobile vehicle.

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.

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.