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Multiple-Point Obstacle Avoidance Based on 3D Depth Camera Skeleton Modeling and Virtual Potential Field for the Redundant Manipulator

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13455))

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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Correspondence to Genliang Xiong .

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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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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13843-0

  • Online ISBN: 978-3-031-13844-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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