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Real-time trajectory planning for collaborative robots using incremental multi-objective optimization

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Abstract

Human–robot collaboration plays a crucial role in industries such as manufacturing, healthcare, and service. It enhances operational efficiency, ensures safety, and optimizes the interaction experience between humans and robots. In close-range human–robot collaboration, trajectory planning for collaborative robots needs to consider the safety, efficiency, and comfort of the trajectory, and be able to respond quickly to changes in the environment. This paper proposes an incremental multi-objective trajectory optimization algorithm. The algorithm integrates real-time human motion data into the optimization problem, ensuring real-time responsiveness to environmental changes during collaboration. Experimental results show that, compared to existing algorithms, our algorithm demonstrates superior overall performance in terms of safety, efficiency, and comfort.

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Authors and Affiliations

  1. Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shangda Road, No.99, Shanghai, Baoshan District, 200444, China

    NanYan Shen, Hua You, Jing Li & Ping Song

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  1. NanYan Shen
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  2. Hua You
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  3. Jing Li
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  4. Ping Song
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Correspondence to Jing Li.

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Shen, N., You, H., Li, J. et al. Real-time trajectory planning for collaborative robots using incremental multi-objective optimization. Intel Serv Robotics 18, 43–59 (2025). https://doi.org/10.1007/s11370-024-00555-0

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