A method and apparatus are disclosed for a clutter tidying robot utilizing floor segmentation for its mapping and navigation system, whereby a perception module and navigation module transform lidar and image data from lidar sensors and cameras of a robot sensing system using segmentation and pseudo-laserscan or point cloud transformations to generate global and local maps. The robot pose and maps are transmitted to a robot brain that directs an action module to produce robot action commands controlling the operation of a clutter tidying robot using the pose and map data. In this manner multi-stage planning and sophisticated obstacle avoidance techniques may be incorporated into autonomous robot operations.

A method (600) for obtaining information about a structure (101) using a drone (102) equipped with a sensor system (103). The method includes, during a first period of time and while the drone's sensor system is pointing towards the structure, using (s602) the sensor system to obtain first depth data. The method also includes obtaining (s604) a first height value, Z1, indicating or being based on the height of the drone above a bottom point of the structure during the first period of time. The method also includes using (s606) the first depth data to determine a first vertical coordinate representing a top point of the structure. The method further includes estimating (s608) a height of the structure, wherein estimating the height of the structure comprises using the first vertical coordinate and the first height value, Z1, to estimate the height of the structure.

The present invention is a battery-powered, remote-controllable rollator with embedded computer systems and computer vision system. The present invention recognizes the user's face by using artificial intelligence technology, namely, the deep convolutional neural networks, and uses that information to localize the rollator's position in relation to the user. An artificial intelligence algorithm computes the motion path and drives the present invention to the user. The present invention can automatically stop once approached to a preset stopping distance from the user. Once stationary, the present invention can then be used by the user.

The invention discloses a method for robots to improve the accuracy of an obstacle labeling, which comprises: making two positionings according to set moments, and then acquiring positioning poses of the two positionings on a grid map respectively at a first moment and a second moment; defining coverage areas of the first and the second moments according to positions of the two positionings, acquiring confidence coefficients of the two positionings, and processing the coverage areas through the confidence coefficients; interpolating the positioning poses, and constructing a closed graph according to the positioning poses, the pose interpolation, and the processed coverage areas; and obtaining a grid occupied by the closed graph on the grid map and modifying the obstacle labeling according to the grid occupied by the closed graph on the grid map and the area of the closed graph.

An information processing apparatus according to an embodiment of the present technology includes: a calculation unit. The calculation unit calculates a self-position of an own device that moves with a moving object, in accordance with a first movement state of a moving object and a second movement state of the own device, on a basis of first movement information relating to the moving object and second movement information relating to the own device. As a result, it is possible to improve detection accuracy. Further, it is possible to improve the accuracy and reliability of the self-position. Since no displacement of the self-position occurs even in a movement space, it is possible for a drone flying in the air to avoid collision with obstacles in the movement space.

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.

The invention proposes a method for the automated discharge of loose transport material from a container, transported by means of a self-driving vehicle, into a collection container, where the unloading takes place in a spatially defined unloading cone within an unloading station. Furthermore, an unloading station for automated discharge according to the method is proposed.

A mobility platform is configured to execute one or more tasks in a worksite including a passive landmark. A mobility platform may include a first laser rangefinder and at least one processor configured to sweep the first passive landmark with the first laser rangefinder to collect a first plurality of distance measurements for a first plurality of yaw angles, fit a first shape to the first plurality of distance measurements based on a predetermined shape of the first passive landmark, and determine a position of a geometric center of the first passive landmark relative to the first location of the first laser rangefinder based on the fit first shape.

A remote control device includes, at least one processer configured to perform processes including, acquiring three-dimensional point cloud data measured using a distance measuring device, estimating at least one of a position and an orientation of a moving object in the three-dimensional point cloud data by matching a template point cloud indicating the moving object with the three-dimensional point cloud data, determining a start position to start matching of the template point cloud with the three-dimensional point cloud data; and generating a control command for remotely controlling the moving object using at least one of the estimated position and the estimated orientation of the moving object and transmit the control command to the moving object.

The present disclosure provides an autonomous mobile device. The autonomous mobile device includes a device main body, provided with a buffer component on a front side of the device main body; a line laser module, arranged on at least one of the device main body and the buffer component and located between the buffer component and the device main body, wherein the line laser module includes a camera device configured to capture an environmental image and a first window is arranged at a position on the buffer component corresponding to the camera device to enable external ambient light to enter the camera device; and an infrared fill-in lamp, arranged on the buffer component