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http://hdl.handle.net/10397/88790
Title: | Control framework for trajectory planning of soft manipulator using optimized RRT algorithm | Authors: | Khan, AT Li, S Kadry, S Nam, Y |
Issue Date: | 2020 | Source: | IEEE access, . . 2020, , v. 8, p. 171730-171743 | Abstract: | This paper proposes a model-free control framework for the path planning of the rigid and soft robotic manipulator using an intelligent algorithm called Weighted Jacobian Rapidly-exploring Random Tree (WJRRT). The optimization approach is used to model the path planning problem, which is independent of the robotic model, and then used the WJRRT algorithm to solve it. WJRRT algorithm not only explores the cartesian space for the end-effector of the robotic manipulator randomly but also directs it towards the goal-position when required. It is robust enough to tackle the uncertainties in the manipulator and make the computation of path planning more efficient. WJRRT assigned a fitness value to each node of the tree. Based on the fitness values algorithm computes the final path, which is a trade-off between efficiency and safety of the path. The simulation results of two, three, and seven degrees of freedom (DOF) robotic manipulators are presented and compared with JT-RRT, Bi-RRT, and TB-RRT algorithms. Experimental results are verified using a soft manipulator made from flexible materials, i.e., polypropylene and polychloroprene. Their flexible structure makes their control complex and creates uncertainties in the model. The simulation and experimental results demonstrate that WJRRT can efficiently and accurately control the motion of manipulators. | Keywords: | Manipulators Soft robotics Path planning Space exploration Jacobian matrices Robustness Rapidly-Exploring random tree Robotic manipulator Redundant manipulator Robust path planning Soft robotics |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE access | EISSN: | 2169-3536 | DOI: | 10.1109/ACCESS.2020.3024630 | Rights: | This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ The following publication Khan, A. T., Li, S., Kadry, S., & Nam, Y. (2020). Control framework for trajectory planning of soft manipulator using optimized RRT algorithm. IEEE Access, 8, 171730-171743 is available at https://dx.doi.org/10.1109/ACCESS.2020.3024630 |
Appears in Collections: | Journal/Magazine Article |
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Khan_Trajectory_Planning_Soft.pdf | 3.1 MB | Adobe PDF | View/Open |
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