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Method for collaborative mapping and locating of multiple robots for large-scale environment

InactiveCN106272423AEliminate Motion Accumulation ErrorsPrecise positioningProgramme-controlled manipulatorAlgorithmMultirobot systems
The invention provides a method for collaborative mapping and locating of multiple robots for a large-scale environment. The method comprises a single-robot laser SLAM algorithm based on a visual detection closed loop, a multi-robot pose constraint estimation algorithm and a multi-robot map fusion algorithm, wherein according to the single-robot laser SLAM algorithm based on the visual detection closed loop, a visual sensor is adopted for assisting a laser sensor in achieving the SLAM algorithm with the more stable roughness. Simultaneous locating and mapping of the multiple robots are achieved through the laser sensor and the visual sensor. The closed loop is detected by obtaining the visual characteristic of the roughness through a camera, and the problem about closed loop detection caused by the robot motion accelerative error is solved effectively; meanwhile through a multi-robot system, simultaneous locating and mapping in the large regional environment are completed efficiently, and the defect that the efficiency is low by means of a single robot is overcome. By the adoption of the method, the precise robot location and map creation of the environment are achieved in the large-scale environment, and the method is also suitable for small-scale environments.
Owner:HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL

Indoor point cloud map generation system and indoor point cloud map generation method based on three-dimensional laser

The invention discloses an indoor point cloud map generation system and an indoor point cloud map generation method based on three-dimensional laser. The indoor point cloud map generation system basedon three-dimensional laser comprises: a data acquisition module, wherein point cloud data is collected by a laser sensor; a data filtration module, wherein noise points and isolated points are filtered by a wave filter; a data registration module, wherein the local point cloud data is subjected to registration by using an image registration method so as to form a completed 3D point cloud map; anda data partition module, wherein the 3D point cloud map is subjected to partition by using a data partition method to obtain the point cloud collection data of different planes and different objects.According to the technical scheme of the present invention, the discrete point cloud data is converted into the complete three-dimensional point cloud map through filtering, splicing, noise reducing,matching, partition and other operations, such that the accurate indoor environment map with the complete three-dimensional structure is established, the accurate and complete map basis is provided for the subsequent navigation and positioning of the robot, and the good scalability and the good stability are provided.
Owner:广州映博智能科技有限公司
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