Abstract
For use in unstructured domains, highly redundant robotic systems need both deliberative and compliant control schemes, to avoid collision and safely interact with the dynamic environment. Aiming at the shortcoming of the traditional method of path planning using merely on the typical structure of the manipulator, a new algorithm, named the “skeleton extraction based on 3D-depth camera”, is proposed for the real-time generation of collision avoidance motions. The algorithm is applied to get the distances of the multiple possible collision points and to establish a new form of a repulsive force, which includes the radial repulsive force and tangential repulsive force. For the redundant manipulator, the equilibrium angles through incremental iteration of the moment instead of inverse kinematics to reduce calculation cost. Finally, the method was tested by a 7-DOF manipulator in MATLAB environment. The results show that the proposed method can avoid local minima traps and eliminate oscillations effectively.
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Seto, F., Kosuge, K., Suda, R., Hirata, Y.: Self-collision avoidance motion control for human Robot cooperation system using RoBE. In: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, Edmonton, Alta, Canada, pp. 3143–3148. IEEE (2005)
De Santis, A., Pierro, P., Siciliano, B.: The multiple virtual end-effectors approach for human-robot interaction. In: Lennarčič, J., Roth, B. (eds.) Advances in Robot Kinematics, pp. 133–144. Springer, Dordrecht (2006). https://doi.org/10.1007/978-1-4020-4941-5_15
Brock, O., Khatib, O.: Elastic strips: a framework for motion generation in human environments. Int. J. Robot. Res. 21(12), 1031–1052 (2002)
Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. Int. J. Robot. Res. 5(1), 90–98 (1986)
Guldner, J., Utkin, V.I.: Sliding mode control for gradient tracking and robot navigation using artificial potential fields. IEEE Trans. Robot. Autom. 11(2), 247–254 (1995)
Yan, P., Yan, Z., et al.: Real time robot path planning method based on improved artificial potential field method. In: Proceedings of the 37th Chinese Control Conference, Wuhan, China, pp. 25–27. IEEE (2018)
Xu, J.J., Duindam, V., Alterovitz, R., Goldberg, K.: Motion planning for steerable needles in 3D environments with obstacles using rapidly-exploring random trees and backchaining. In: 4th IEEE Conference on Automation Science and Engineering Key Bridge Marriott, Washington DC, USA, pp. 41–46. IEEE (2008)
Kavralu, L.E., Svestka, P., Latombe, J.C., Overmars, M.H.: Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Trans. Robot. Autom. 12(4), 566–580 (1996)
Tzafestas, S.G., Tzamtzi, M.P., Rigatos, G.G.: Robust motion planning and control of mobile robots for collision avoidance in terrains with moving objects. Math. Comput. Simul. 59(4), 279–292 (2002)
Ge, S.S., Cui, Y.J.: Dynamic motion planning for mobile robots using potential field method. Auton. Robot. 13, 207–222 (2002)
Weerakoon, T., Ishii, K., Forough Nassiraei, A.A.: An artificial potential field based mobile robot navigation method to prevent from deadlock. J. Artif. Intell. Soft Comput. Res. 5(3), 189–203 (2015)
Wang, Q.Z., Cheng, J.Y., Li, X.L.: Path planning of robot based on improved artificial potentional field method. In: Proceedings of the 2017 International Conference on Artificial Intelligence, Automation and Control Technologies, Wuhan, China, pp. 1–6 (2017)
Li, H., Wang, Z.Y., Ou, Y.S.: Obstacle avoidance of manipulators based on improved artificial potential field method. In: Proceeding of the IEEE International Conference on Robotics and Biomimetics, Dali, China, pp. 564–569 (2019)
Zhu, Z.X., Jing, S., Zhong, J.F., Wang, M.: Obstacle avoidance path planning of space redundant manipulator based on a collision detection algorithm. J. Northwestern Polytech. Univ. 38(1), 183–189 (2020)
Oscar, M., Ulises, O.R., Roberto, S.: Path planning for mobile robots using bacterial potential field for avoiding static and dynamic obstacles. Expert Syst. Appl. 42(12), 5177–5191 (2015)
Badawy, A.: Dual-well potential field function for articulated manipulator trajectory planning. Alex. Eng. J. 55(2), 1235–1241 (2016)
Huber, L., Billard, A., Slotine, J.: Avoidance of convex and concave obstacles with convergence ensured through contraction. IEEE Robot. Autom. Lett. 4(2), 1462–1469 (2019)
He, Z.C., He, Y.L., Zeng, B.: Obstacle avoidance path planning for robot arm based on mixed algorithm of artificial potential field method and RRT. Ind. Eng. J. 20(2), 56–63 (2017)
Zhu, J., Yang, M.Y.: Path planning of manipulator to avoid obstacle based on improved artificial potential field method. Comput. Meas. Control 26(10), 205–210 (2018)
Xie, L., Liu, S.: Dynamic obstacle-avoiding motion planning for manipulator based on improved artificial potential filed. Control Theory Appl. 35(9), 1239–1249 (2018)
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Xiong, G., Ye, L., Zhang, H., Yanfeng, G. (2022). Multiple-Point Obstacle Avoidance Based on 3D Depth Camera Skeleton Modeling and Virtual Potential Field for the Redundant Manipulator. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13455. Springer, Cham. https://doi.org/10.1007/978-3-031-13844-7_4
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DOI: https://doi.org/10.1007/978-3-031-13844-7_4
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