A robot cleaner is disclosed. The robot cleaner comprises: a wireless communication module comprising wireless communication circuitry; a UWB communication module comprising UWB communication circuitry; and at least one processor, comprising processing circuitry, individually and/or collectively, configured to: identify whether at least one electronic device capable of UWB communication and at least one electronic device capable of wireless communication are present in a space where the robot cleaner is located, and based on the presence of a first electronic device capable of UWB communication and a second electronic device capable of wireless communication being identified, identify a first distance between the first electronic device and the robot cleaner using the UWB communication module, identify a second distance between the second electronic device and the robot cleaner using the wireless communication module, identify a third distance between a charging station, located in the space and capable of UWB communication, and the robot cleaner using the UWB communication module, and identify the location of the robot cleaner based on the first distance, the second distance, the third distance, the location of the first electronic device, the location of the second electronic device, and the location of the charging station, wherein wireless communication includes a communication scheme different from UWB communication.

A robot cleaner includes a body to travel on a floor; an obstacle sensing unit to sense an obstacle approaching the body; an auxiliary cleaning unit mounted to a bottom of the body, to be extendable and retractable; and a control unit to control extension or retraction of the auxiliary cleaning unit when the obstacle is sensed. The control unit prevents the auxiliary cleaning unit from extending if a signal is received from a charger.

A method of operating a mobile robot includes generating a segmentation map defining respective regions of a surface based on occupancy data that is collected by a mobile robot responsive to navigation of the surface, identifying sub-regions of at least one of the respective regions as non-clutter and clutter areas, and computing a coverage pattern based on identification of the sub-regions. The coverage pattern indicates a sequence for navigation of the non-clutter and clutter areas, and is provided to the mobile robot. Responsive to the coverage pattern, the mobile robot sequentially navigates the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern. Related methods, computing devices, and computer program products are also discussed.

Embodiments of the present disclosure provide a distance measurement method and device, a robot and a storage medium. The method comprises: acquiring a first image, where the first image at least comprises a to-be-detected object and a ground on which the to-be-detected object is located; determining an initial constraint condition of the ground based on the first image; acquiring a second image, where the second image at least comprises an intersection line of a line structured light beam with the ground and/or with the to-be-detected object; determining a position parameter of the ground based on the second image, and correcting the initial constraint condition of the ground based on the position parameter; and determining a distance to the to-be-detected object based on the corrected initial constraint condition of the ground and the first image.

The present disclosure relates to the technical field of smart home, and in particular, to a floor material recognition method, a control method, and a storage medium. The recognition method for the autonomous mobile device for recognizing the floor material includes: transmitting control instructions to the autonomous mobile device, the control instructions including commands that instruct the autonomous mobile device to rotate at a same location for a predetermined rotation angle; obtaining an actual rotation angle of the autonomous mobile device; determining a floor material based on the predetermined rotation angle and the actual rotation angle, such that the autonomous mobile device can automatically recognize different floor materials, and execute different functions or work modes, or automatically configure different set velocities based on the different floor materials, such that the autonomous mobile device can reach substantially consistent actual moving velocities when moving on the different floor materials.

The present application discloses a robot task execution method, apparatus, robot and storage medium. The method comprises: acquiring a training trajectory and an environment map in a training mode; generating a target region for tasks to be performed by a robot based on the environment map and the training trajectory, wherein the target region is a maximum envelope region in which the robot can complete tasks autonomously; controlling the robot to traverse the target region until the robot completes the tasks to be performed. By adopting the above technical solution, the robot can perform tasks stably and efficiently in various environmental regions, thereby being able to be applied to various application scenarios.

The application provides a structured light module and an autonomous mobile device. The structured light module includes a first camera and line laser emitters for collecting a first environmental image containing laser stripes generated when the line laser encounters an object. The structured light module can also capture a visible light image through a second environmental image that does not contain laser stripes. Both the first and second environmental images can help to detect more accurate and richer environmental information, expanding the application range of laser sensors.

Disclosed in the embodiments of the present disclosure are a navigation method of a robot, a chip and a robot. In the navigation method, when the position of the robot is not communicated with a preset known grid area constructed before relocalization, and grids allowing the robot to pass are marked within a detectable distance of a sensor of the robot, so as to plan a navigation path for enabling the robot to actually walk into the preset known grid area.

A GPS directed vehicle for cleaning airport runway surfaces. The vehicle uses an ultra-high pressure washer for cleaning rubber off the surfaces of the runway, and a vacuum system for the collection of debris. A GPS device allows an operator to track a cleaning line so as to allow no more than 25 mm overlap of surfaces to be cleaned. An iPad can be used to highlight Google maps for calculating a runway area to be treated. Recording allows the exact location of last treated surface area to allow exact location of an untreated surface area.

A linear laser module and a self-moving device are provided. The linear laser module is applied for the self-moving device, and includes: a camera apparatus for acquiring an ambient image; at least one linear laser emitter, disposed on both sides of the camera apparatus, and configured to emit a laser having a linear projection, the camera apparatus working in coordination with the at least one linear laser emitter; and a return-to-pile positioning apparatus for receiving a first infrared signal emitted by a charging pile. Thereby, a sensing component communicatively connected to the charging pile, and a sensing component for measuring a road condition in front of a device body, are integrated into the linear laser module, thereby allowing a modular design of a sensing system, which is convenient for assembly and repair.