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Trajectory Planning with Collision Avoidance for Redundant Robots Using Jacobian and Artificial Potential Field-based Real-time Inverse Kinematics

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Abstract

This study proposes an algorithm for combining the Jacobian-based numerical approach with a modified potential field to solve real-time inverse kinematics and path planning problems for redundant robots in unknown environments. With an increase in the degree of freedom (DOF) of the manipulator, however, the problems in realtime inverse kinematics become more difficult to solve. Although the analytical and geometrical inverse kinematics approach can obtain the exact solution, it is considerably difficult to solve as the DOF increases, and it necessitates recalculations whenever the robot arm DOF or Denavit-Hartenberg (D-H) parameters change. In contrast, the numerical method, particularly the Jacobian-based numerical method, can easily solve inverse kinematics irrespective of the aforementioned changes including those in the robot shape. The latter method, however, is not employed in path planning for collision avoidance, and it presents real-time calculation problems. This study accordingly proposes the Jacobian-based numerical approach with a modified potential field method that can realize real-time calculations of inverse kinematics and path planning with collision avoidance irrespective of whether the case is redundant or non-redundant. To achieve this goal, the use of a judgment matrix is proposed for obstacle condition identification based on the obstacle boundary definition; an approach for avoiding the local minimum is also proposed. After the obstacle avoidance path is generated, a trajectory plan that follows the path and avoids the obstacle is designed. Finally, the proposed method is evaluated by implementing a motion planning simulation of a 7-DOF manipulator, and an experiment is performed on a 7-DOF real robot.

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Authors and Affiliations

  1. School of Mechanical Engineering, Pusan National University, 2, Busandaehakro 63beon-gil, Geumjeong-gu, Busan, Korea

    Sun-Oh Park, Min Cheol Lee & Jaehyung Kim

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  1. Sun-Oh Park
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  3. Jaehyung Kim
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Correspondence to Min Cheol Lee.

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Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Kang-Hyun Jo under the direction of Editor Keum-Shik Hong. This work was supported by the Technology Innovation Program(10073147, Development of Robot Manipulation Technology by Using Artificial Intelligence) funded By the Ministry of Trade, Industry & Energy(MOTIE, Korea). This research was also funded and conducted under “the Competency Development Program for Industry Specialists” of the Korean Ministry of Trade, Industry and Energy (MOTIE), operated by Korea Institute for Advancement of Technology (KIAT) (No. P0008473, The development of high skilled and innovative manpower to lead the Innovation based on Robot).

Sun-Oh Park is working towards the completion of his M.S. degree in Mechanical Engineering from Pusan National University, Busan, Korea since 2017. He received his B.S. degree in Mechanical Engineering from Pusan National University, Busan, Korea in 2015. His research interests include intelligent robot control, dynamics, machine learning, machine vision, development path planning. autonomous robots and simulation.

Min Cheol Lee received his Ph.D. degree in Applied Physics from the University of Tsukuba, Tsukuba, Japan in 1991, M.S. degree in Engineering Science from the University of Tsukuba, Tsukuba, Japan in 1988, and B.S. degree in Mechanical Engineering from Pusan National University, Busan, Korea in 1983. He was a visiting professor at North Carolina State University from Aug. 2000 to Aug. 2001 and at Purdue University from Aug. 2009 to Aug. 2010. From 1991 to present, he is a professor in the School of Mechanical Engineering from Pusan National University, Korea. His research interests include intelligent robot control, autonomous mobile robot, medical robotics, system identification, sliding mode control, and navigation/localization of mobile robots.

Jaehyung Kim is working towards the completion of his M.S. degree in Mechanical Engineering from Pusan National University, Busan, Korea since 2019. He received his B.S. degree in Mechanical Engineering from Pusan National University, Busan, Korea in 2019. His research interests include intelligent robot control, kinematics, machine learning, machine vision, path planning and autonomous robots and simulation.

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Park, SO., Lee, M.C. & Kim, J. Trajectory Planning with Collision Avoidance for Redundant Robots Using Jacobian and Artificial Potential Field-based Real-time Inverse Kinematics. Int. J. Control Autom. Syst. 18, 2095–2107 (2020). https://doi.org/10.1007/s12555-019-0076-7

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