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Spline-Based RRT Path Planner for Non-Holonomic Robots

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Abstract

Planning in a cluttered environment under differential constraints is a difficult problem because the planner must satisfy the external constraints that arise from obstacles in the environment and the internal constraints due to the kinematic/dynamic limitations of the robot. This paper proposes a novel Spline-based Rapidly-exploring Random Tree (SRRT) algorithm which treats both the external and internal constraints simultaneously and efficiently. The computationally expensive numerical integration of the system dynamics is replaced by an efficient spline curve parameterization. In addition, the SRRT guarantees continuity of curvature along the path satisfying any upper-bounded curvature constraints. This paper presents the underlying theory to the SRRT algorithm and presents simulation and experiment results of a mobile robot efficiently navigating through cluttered environments.

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Authors and Affiliations

  1. Department of Aerospace and Mechanical Engineering, Korea Air Force Academy, Cheongwon, Republic of Korea

    Kwangjin Yang & Sangwoo Moon

  2. Department of Electrical Engineering and Computer Science, Korea Air Force Academy, Cheongwon, Republic of Korea

    Seunghoon Yoo

  3. School of Electrical Engineering, Korea University, Seoul, Republic of Korea

    Jaehyeon Kang & Nakju Lett Doh

  4. Future Man Electronics, Daejon, Republic of Korea

    Hong Bong Kim

  5. Agency for Defense Development, Daejon, Republic of Korea

    Sanghyun Joo

Authors
  1. Kwangjin Yang
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  2. Sangwoo Moon
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  3. Seunghoon Yoo
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  4. Jaehyeon Kang
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  5. Nakju Lett Doh
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  6. Hong Bong Kim
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  7. Sanghyun Joo
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Corresponding author

Correspondence to Kwangjin Yang.

Additional information

This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2012R1A1A4A01005563).

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Yang, K., Moon, S., Yoo, S. et al. Spline-Based RRT Path Planner for Non-Holonomic Robots. J Intell Robot Syst 73, 763–782 (2014). https://doi.org/10.1007/s10846-013-9963-y

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  • DOI: https://doi.org/10.1007/s10846-013-9963-y

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