A robot (100) working area map construction method and apparatus, a robot (100), and a medium, wherein the robot (100) working area map construction method comprises scanning in real time an obstacle in a driving path and recording position parameters of the obstacle (S102); obtaining in real time image information of the obstacle in the driving path (S104); according to the position parameters and the image information, determining working area—based reference information of the obstacle (S106); and dividing the working area into a plurality of sub-areas on the basis of the reference information (S108). By means of radar scanning and image capture by a camera for double insurance, the robot (100) working area map construction method significantly improves recognition accuracy for room doors and avoids room division confusion caused by the incorrect recognition of doors.

A moving range of an object is estimated on the basis of image information. An information processing apparatus includes an input unit that inputs an image, a region estimation unit that estimates a region of an object contained in the image, a moving history information acquisition unit that acquires information associated with a moving history of the object, a contact region determination unit that determines a contact region in contact with the object on the basis of an estimation result obtained by the region estimation unit, and a moving range estimation unit that estimates a moving range of the object on the basis of the moving history containing the contact region of the object. The moving range estimation unit estimates the moving range of the object on the basis of the moving history containing the contact region of the object and a moving track of the object.

Picking devices for operating a picking devices for medicaments are provided. A picking device includes multiple storage spaces for medicament packaging, an operating device movable horizontally in an X-direction and vertically in a Z-direction in front of the storage spaces in a movement space, and an identification device configured for identifying medicament packaging. An optical detection device is configured to create an overall image of the movement space and a control device is coupled to the operating device, the identification device and the optical detection device, wherein the control device is configured to determine the presence of an obstacle in a portion of the movement space and to control the operating device based on the determined presence of the obstacle. Methods of operating picking devices for medicaments are also provided.

The disclosure provides an environment perception device and method of a mobile vehicle. The environment perception device includes a camera module, a LiDAR module, a database and a processing circuit. The camera module photographs a field near the mobile vehicle to generate a three-dimensional (3D) image frame. The LiDAR module scans the field to generate a 3D scanned frame. The processing circuit fuses the 3D image frame and the 3D scanned frame to generate 3D object information. The processing circuit compares the 3D object information with a 3D map in the database to determine whether an object is a static object. The processing circuit performs an analysis and calculation on the 3D object information to obtain movement characteristics of the object when the object is not the static object, and skips the analysis and calculation on the 3D object information when the object is the static object.

A machine may receive, from one or more sensors, first data indicating a first position of a work implement within an environment and second data indicating a second position of the work implement within the environment. Based on the first position and the second position, the machine may define a working area of the work implement. The machine may receive, from one or more cameras, image data depicting at least a portion of the environment and at least a portion an object disposed within a field of view of the one or more cameras. The machine may determine, based on the image data, that the object is located outside of the working area. Based on determining that the object is located outside of the working area, the machine may refrain from causing output of an alert indicating the presence of the object outside the working area.

A device for controlling a vehicle may include a sensor that senses an object around the vehicle and acquires travel information of the vehicle, and a controller that creates an integrated line corresponding to a road where the vehicle is traveling, and sets a region of interest corresponding to the object based on the integrated line, and changes the region of interest based on the travel information of the vehicle.

A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

An object detection system for a vehicle includes a camera vision module and a Lidar module. The camera vision module includes an imaging device viewing to the exterior of the vehicle and operable to capture image data representative of a scene exterior and forward of the vehicle. The Lidar module includes a Lidar device that, with the Lidar module mounted at a front exterior portion of the vehicle, scans a region forward of the vehicle that overlaps with the field of view of the imaging device. Based at least in part on processing of captured image data by an image processor and based at least in part on processing of Lidar data captured by the Lidar device, 3-dimensional and timing information relative to the vehicle of objects present exterior of the vehicle is algorithmically constructed. At least one individual object of the multiple objects is prioritized.

Techniques are discussed for controlling a vehicle, such as an autonomous vehicle, based on occluded areas in an environment. An occluded area can represent areas where sensors of the vehicle are unable to sense portions of the environment due to obstruction by another object. An occlusion grid representing the occluded area can be stored as map data or can be dynamically generated. An occlusion grid can include occlusion fields, which represent discrete two- or three-dimensional areas of driveable environment. An occlusion field can indicate an occlusion state and an occupancy state, determined using LIDAR data and/or image data captured by the vehicle. An occupancy state of an occlusion field can be determined by ray casting LIDAR data or by projecting an occlusion field into segmented image data. The vehicle can be controlled to traverse the environment when a sufficient portion of the occlusion grid is visible and unoccupied.

A mobile robot and a method of controlling the mobile robot are disclosed. The method includes acquiring an image of an inside of a traveling zone. The method further includes performing a point-based feature point extraction by extracting a first feature point from the acquired image. The method also includes performing a block-based feature point extraction by dividing the acquired image into blocks having a predetermined size and extracting a second feature point from each of the divided block-unit images. The method also includes determining the current location by performing a point-based feature point matching using the first feature point and performing a block-based feature point using the second feature point. The method also includes storing the determined current location in association with the first feature point and the second feature point in a map.