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Real-Time and Efficient Collision Avoidance Planning Approach for Safe Human-Robot Interaction

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Abstract

With the rapid development of robot perception and planning technology, robots are gradually getting rid of fixed fences and working closely with humans in a shared workspace. The safety of human-robot coexistence becomes critical. Although various safety-related motion planning methods have been proposed to prevent robots from colliding with obstacles, collision avoidance planning in highly dynamic environments is still an open problem. In this paper, we propose a robust and efficient collision avoidance planning method that generates a collision-free trajectory in real-time by leveraging the complementary strengths of the potential field and optimization. Our approach starts with a new repulsive force generation method that quickly generates collision avoidance actions even if obstacles are moving faster than the robot. To ensure that the robot avoids collisions while converging toward the goal, an optimization method based on quadratic programming is designed to minimize the deviation of the post-optimized trajectory from the reference trajectory by fusing the whole body collision avoidance constraints and constraints dimensionality reduction. Finally, a closed-loop safety protection framework is presented, including obstacle perception, collision avoidance planning, and multi-task optimization. Compared with the existing state-of-the-art collision avoidance planners as well as advanced trajectory optimization methods, our method can generate a shorter collision-free trajectory in less time with a higher success rate. Detailed simulation comparison experiments, as well as real-world comparison experiments, are reported to verify the effectiveness of our method.

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Code generated or used during the study is available from the corresponding author on reasonable request.

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Funding

This work was supported in part by the Science and Technology Plan of Liaoning Province-Major Industrial Project under Grant 2019JH1/10100005, in part by the National Key R&D Program of China under Grant 2017YFB1301100, and in part by the Xingliao Talents Program of Liaoning Province under Grant XLYC1807110, and in part by the “Hundreds, Thousands, Thousands of Talents Project” Funded Project of Liaoning Province under Grant 2020921001.

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Authors and Affiliations

  1. State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, 110169, Shenyang, China

    Hongyan Liu, Daokui Qu, Fang Xu, Kai Jia & Jilai Song

  2. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, 110169, Shenyang, China

    Hongyan Liu, Daokui Qu, Fang Xu, Kai Jia & Jilai Song

  3. University of Chinese Academy of Sciences, Beijing, 100049, China

    Hongyan Liu

  4. SIASUN Robot & Automation CO.,Ltd, Shenyang, 110169, China

    Daokui Qu, Fang Xu, Zhenjun Du, Kai Jia, Jilai Song & Mingmin Liu

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  1. Hongyan Liu
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  2. Daokui Qu
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  3. Fang Xu
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Contributions

Conceptualization: Hongyan Liu; Methodology: Hongyan Liu; Formal analysis and investigation: Xiaofeng Wang; Writing - original draft preparation: Hongyan Liu; Writing - review and editing: Zhenjun Du, Jilai Song, Mingmin Liu; Funding acquisition: Zhenjun Du; Resources: Fang Xu, Zhenjun Du; Supervision: Daokui Qu, Fang Xu.

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Correspondence to Hongyan Liu.

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Liu, H., Qu, D., Xu, F. et al. Real-Time and Efficient Collision Avoidance Planning Approach for Safe Human-Robot Interaction. J Intell Robot Syst 105, 93 (2022). https://doi.org/10.1007/s10846-022-01687-0

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