Task Space Vector Field Guiding for Motion Planning
Fernando Urra Gonzalez, Jan Rosell, Raúl Suárez · 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA) · 2022
The article deals with the problem of planning in the task space in the presence of vector fields, while verifying and validating the constraints in the configuration space. The proposed approach, called the Task Space Vector Field Rapidly-exploring Random Tree (TSVF-RRT) algorithm, extends the Task-Space Rapidly-exploring Random Trees (TS-RRT) algorithm by incorporating vector fields into the task space, while avoiding non-trivial constraints on the configuration space. The planner restricts the search to a lower dimensional space, minimizing the upstream functional. To evaluate the proposed approach, graphical simulations are presented, carried out using a planar manipulator of 10 DOF. Possible advantages that encourage further research in this line are discussed.