A method for use in a robotic work tool (100) arranged to operate in an operational area, the robotic work tool comprising a memory configured to store a location of at least one object, a distance sensor (195), a navigation sensor (185) being based on signal-reception and a controller, the method comprising:determining a location of the robotic work tool (100) utilizing the navigation sensor (185);determining that a shadowed area is encountered, wherein navigation utilizing the navigation sensor is not reliable; andin response thereto navigating utilizing the distance sensor based on detecting at least one object and a distance to the at least one object utilizing the distance sensor (195), the stored at least one object and the location of the robotic work tool (100).

A description is given of a method for an autonomous mobile robot (AMR). According to one exemplary embodiment, the method comprises navigating the AMR through an operational area with the aid of one or more navigation sensors: acquiring information about the surroundings of the AMR in the operational area: automatically detecting subareas within the operational area and classifying the detected subareas by way of a classifier based on the acquired information wherein an area class is determined: and storing detected subareas, including the ascertained area class, in an electronic map of the AMR.

A prism for reflecting a laser includes: a single mounting cap at a first end of the prism, and first to seventh trihedral corner (TC) reflectors, each including a reflective surface including: three side edges, and three corners at respective intercept points between the side edges, wherein the seventh TC reflector, among the first to seventh TC reflectors, is on a second end of the prism opposite to the first end of the prism.

An automatic transfer system includes a guide path, a transfer vehicle, and a program for calculation of a travel route of the transfer vehicle. Each of a plurality of branch points and a plurality of stop positions included in the guide path is assigned with any one of position codes specified by a combination of three numbers, which is a number of pieces corresponding to a maximum order of channels included in the guide path. Each of three numbers specifying the position code is determined on the basis of a channel including a branch point or a stop position corresponding to the position code and on the basis of a sequential order of the branch point or the stop position from a start point of the channel.

A positioning method for a ceiling vision robot are provided. The method includes: during a moving process, a ceiling vision robot acquiring a ceiling image in real time; acquiring existing road sign distribution information according to the ceiling image; determining whether to establish a new road sign, according to the existing road sign distribution information, and if so, establishing a new road sign at a acquisition position of the ceiling image, and if not, not establishing the new road sign at the acquisition position of the ceiling image; and monitoring the positioning effectiveness of an existing road sign according to the existing road sign distribution information, and if the positioning of the existing road sign is effective, performing positioning by using pose information corresponding to the existing road sign, and if the positioning of the existing road sign is ineffective, not performing positioning by using the pose information corresponding to the existing road sign. In the method, a ceiling vision robot is used to avoid a situation in which the environment is complex and road signs are thus easily confused; a new road sign is established according to existing road sign distribution information, thereby realizing the uniformly establishment of road signs; and effectiveness detection is performed on an existing-road sign, thereby improving the precision of positioning based on road signs.

Systems and methods for detecting, mapping, and route planning around cliffs for robotic devices are disclosed herein. According to at least one non-limiting exemplary embodiment, a robot processing a three-dimensional range sensor scan may utilize pre-computed neighboring points to detect cliffs, navigable ramps, and holes in a plane of a map used by the robotic device to navigate.

A robot includes a 2D camera, a 1D distance sensor, a driving module configured to move the robot, and at least one processor. The at least one processor is configured to: obtain a 2D image by controlling the 2D camera; calculate relative depths of actual regions indicated by pixels in the 2D image, based on the obtained 2D image; obtain a reference distance to a point to which a laser output from the 1D distance sensor is irradiated; determine a distance from the robot to the object in the 2D image based on the obtained reference distance and a relative depth of a reference point corresponding to the point to which the laser is irradiated among the pixels in the 2D image; and travel based on the determined distance to the object.

A control device includes a direction identifying data generator that generates direction identifying data including at least a portion of acquired point group data indicating a position of a region including the ridge in front of an agricultural vehicle in a traveling direction, a direction identification part that identifies a direction of the ridge on the basis of the direction identifying data, and a travel control part that controls the agricultural vehicle such that the agricultural vehicle travels in the direction of the ridge identified by the direction identification part.

A robot control method, including: determining a target operation map according to target position information of a current operation of a robot; determining, based on a pre-established map connection relationship, a transfer position that the robot moves to; controlling the robot to move to the transfer position and switching maps, until the robot moves to the target operation map; and controlling the robot to move to an operation destination according to map information of the target operation map and the target position information.

An own-position estimating device for estimating an own-position of a moving body by matching a feature extracted from an acquired image with a database in which position information and the feature are associated with each other in advance, includes an estimating unit estimating the own-position of the moving body by matching the feature extracted by the extracting unit with the database, and a determination threshold value adjusting unit adjusting a determination threshold value for extracting the feature, in which the determination threshold value adjusting unit acquires the database in a state in which the determination threshold value is adjusted, and adjusts the determination threshold value on the basis of the determination threshold value linked to each of the position information items in the database, and the extracting unit extracts the feature from the image by using the determination threshold value adjusted by the determination threshold value adjusting unit.