The International Journal of Robotics Study, Ahead of Publish.
This job presents the BoundMPC method, an ingenious on the internet model-predictive path-following technique for robotic manipulators. This joint-space trajectory organizer enables the following of Cartesian referral courses in the end-effector’s setting and alignment, consisting of via-points, within the wanted uneven bounds of the orthogonal course mistake. These bounds inscribe the obstacle-free room and extra task-specific restraints in Cartesian room. As opposed to typical path-following principles, BoundMPC actively differs the Cartesian referral course ready and alignment to represent the robotic’s kinematics, bring about even more effective job implementations for Cartesian referral courses. Moreover the basic referral course formula is computationally effective and permits replanning throughout the robotic’s activity. This function makes it feasible to utilize this organizer for dynamically altering atmospheres and differing objectives. The adaptability and efficiency of BoundMPC are experimentally shown by 5 situations on a 7-DoF Kuka LBR iiwa 14 R820 robotic. The very first circumstance reveals the transfer of a bigger item from a beginning to an objective posture via a restricted room where the item have to be slanted. The 2nd circumstance manage understanding a things from a table where the understanding factor modifications throughout the robotic’s activity, and accidents with various other barriers in the scene have to be prevented. The versatility of BoundMPC is showcased in situations such as the opening of a cabinet, the transfer of an open container, and the cleaning of a table, where it efficiently deals with task-specific restraints. The last circumstance highlights the opportunity of audit for accidents with the whole robotic’s kinematic chain. The code is easily offered at https://github.com/TU-Wien-ACIN-CDS/BoundMPC, motivating you to discover its possible and adjust it to your particular robot jobs.
发布者：Thies Oelerich，转转请注明出处：https://robotalks.cn/boundmpc-cartesian-path-following-with-error-bounds-based-on-model-predictive-control-in-the-joint-space/
