A method for determining an energy-efficient path of an autonomous device wherein said autonomous device moves over a global grid of cells into which a given operating area has been split, the method being characterized in that determination of said energy-efficient path comprises the steps of: processing of the current cell (201); taking a measurement σ of the processing (202); classifying the measurement σ to be of a particular level Σ (203), taking into account a predefined division, of the measurements results range, into a plurality of measurements levels; storing said classified measurement in a memory of the autonomous device (204) and associating it with the current cell; selecting a reference probability grid (205); updating (207) the probabilities by applying the reference grid (100) to the global grid at its current position such that every cell on the reference grid (100) corresponds unambiguously to one cell on the global grid;

and moving the autonomous device to a next cell of the global grid (208) and setting said next cell as the current cell (201) in order to process the next cell.

An autonomous ground treatment appliance, in particular a robotic lawnmower, includes a housing, a running gear, a control unit, at least one wheel unit, and a sensor unit. The control unit is configured to control the autonomous ground treatment appliance. The at least one wheel unit is mounted on the housing so as to be at least partially movable relative to the housing. The sensor unit is configured to ascertain a position of the wheel unit relative to the housing.

A self-moving device, including: a moving module, a task execution module, a control module. The control module is electrically connected to the moving module and the task execution module, controls the moving module to actuate the self-moving device to move, controls the task execution module to execute a working task. The self-moving device further includes a satellite navigation apparatus, electrically connected to the control module and configured to receive a satellite signal and output current location information of the self-moving device. The control module determines whether quality of location information output by the satellite navigation apparatus at a current location satisfies a preset condition, controls, if the quality does not satisfy the preset condition, the moving module to actuate the self-moving device to change a moving manner, to enable quality of location information output by the satellite navigation apparatus at a location after the movement to satisfy the preset condition.

Autonomous machine navigation involves determining a current pose of an autonomous machine based on non-vision-based pose data captured by one or more non-vision-based sensors of the autonomous machine. The pose represents one or both of a position and an orientation of the autonomous machine in a work region defined by one or more boundaries. Pose data is determined based on a return signal received in response to a wireless signal transmitted to a surface or subsurface object that passively provides the return signal. The return signal is identifiable with the object. The current pose is updated based on the pose data to correct or localize the current pose and to provide an updated pose of the autonomous machine in the work region.

According to one embodiment, provided is a method for controlling a system comprising a lawn mower robot, the method comprising: a boundary setting driving step wherein the lawn mower robot drives in order to set a boundary of a target work area in which at least three anchors are installed on the boundary thereof; a shadow area determination step wherein, in the boundary setting driving step, the lawn mower robot receives a signal from the anchors and sets, as a shadow area, an area where the signal cuts off; a driving ending step wherein when the lawn mower robot returns to an initial position, the boundary setting driving step is ended, and driving information received from the anchors is stored; an information transmission step for transmitting, to a simulator, the driving information and information on the shadow area and the target work area; an obstacle map generation step for generating, by the simulator, an obstacle map on the basis of the shadow area of each anchor; a screen output step wherein the simulator overlaps an externally provided map and the obstacle map, and outputs same on a screen; and an anchor recommending step for recommending, to a user, positions at which the size of the shadow areas identified within the target work area can be minimized. According to the present embodiment, a user can easily check whether the anchor installation positions are desirable.

This invention relates to an information management system of lawn profile data. It comprises a lawn profile information collecting tool for collecting information any pieces of lawns that need mowing jobs; wherein the lawn profile information collecting tool includes a data converter for converting such information to lawn profile data, and data processer for processing the lawn profile data locally into suitable formats and categories for uploading; a mobile device of a user being in communication with the lawn profile information collecting tool to receive the processed lawn profile data; a remote information processing center being in communication with the mobile device and the lawn profile information collecting tool to receive and process requests from the mobile device to upload the lawn profile data; wherein the remote information processing center includes a data storage unit for storing the lawn profile data for usage thereof by a designated lawn mower to perform mowing job, that is, using the stored lawn profile data associated with the particular piece of lawn as requested.

An integrated navigation method for a mobile vehicle is provided, which includes: acquiring a motion measurement of the mobile vehicle by using an inertial navigation element in the mobile vehicle and calculating a gesture parameter of the mobile vehicle based on the motion parameter; estimating, based on the gesture parameter, a motion state of the mobile vehicle in a real time manner by using a satellite navigation element in the mobile vehicle to obtain an error estimation value of the motion state, and correcting a motion parameter of the mobile vehicle based on the error estimation value of the motion state; and controlling an operation route of the mobile vehicle based on corrected navigation information.

A mobile robot and a method of controlling the same are provided, and more specifically, a technology of automatically generating a map of a lawn working area by a lawn mower robot. The mobile robot includes one or more tags configured to receive a signal from one or more beacons, a vision sensor configured to distinguish and recognize a first area and a second area on a travelling path of the mobile robot and acquire position information of a boundary line between the first area and the second area, and at least one processor configured to determine position coordinates of the mobile robot based on pre-stored position information of the one or more beacons, determine position coordinates of the boundary line based on the determined position coordinates of the mobile robot and the acquired position information of the boundary line, and generate a map of the first area while travelling along the determined position coordinates of the boundary line.

The present specification relates to a mobile robot system and a boundary information generation method for the mobile robot system, the mobile robot system comprising a signal processing device that comprises a receiving tag for receiving a transmission signal and a distance sensor, so as to recognize coordinate information about a spot at which the point of the distance sensor is designated on the basis of the reception result of the receiving tag and the distance measurement result of the distance sensor, thereby generating boundary information according to the path designated as the point of the distance sensor on the basis of the recognized coordinate information.

Vision systems for autonomous machines and methods of using same during machine localization are provided. Exemplary systems and methods may reduce computing resources needed to perform vision-based localization by selecting the most appropriate camera from two or more cameras, and optionally selecting only a portion of the selected camera's field of view, from which to perform vision-based location correction. Other embodiments may provide camera lens coverings that maintain optical clarity while operating within debris-filled environments.