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Grasping Trajectory Optimization with Point Clouds
March 11, 2024, 4:45 a.m. | Yu Xiang, Sai Haneesh Allu, Rohith Peddi, Tyler Summers, Vibhav Gogate
cs.CV updates on arXiv.org arxiv.org
Abstract: We introduce a new trajectory optimization method for robotic grasping based on a point-cloud representation of robots and task spaces. In our method, robots are represented by 3D points on their link surfaces. The task space of a robot is represented by a point cloud that can be obtained from depth sensors. Using the point-cloud representation, goal reaching in grasping can be formulated as point matching, while collision avoidance can be efficiently achieved by querying …
abstract arxiv cloud cs.cv cs.ro grasping optimization point-cloud representation robot robotic robots space spaces trajectory type
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