{"ID":2882671,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.09581","arxiv_id":"2508.09581","title":"ESCoT: An Enhanced Step-based Coordinate Trajectory Planning Method for Multiple Car-like Robots","abstract":"Multi-vehicle trajectory planning (MVTP) is one of the key challenges in multi-robot systems (MRSs) and has broad applications across various fields. This paper presents ESCoT, an enhanced step-based coordinate trajectory planning method for multiple car-like robots. ESCoT incorporates two key strategies: collaborative planning for local robot groups and replanning for duplicate configurations. These strategies effectively enhance the performance of step-based MVTP methods. Through extensive experiments, we show that ESCoT 1) in sparse scenarios, significantly improves solution quality compared to baseline step-based method, achieving up to 70% improvement in typical conflict scenarios and 34% in randomly generated scenarios, while maintaining high solving efficiency; and 2) in dense scenarios, outperforms all baseline methods, maintains a success rate of over 50% even in the most challenging configurations. The results demonstrate that ESCoT effectively solves MVTP, further extending the capabilities of step-based methods. Finally, practical robot tests validate the algorithm's applicability in real-world scenarios.","short_abstract":"Multi-vehicle trajectory planning (MVTP) is one of the key challenges in multi-robot systems (MRSs) and has broad applications across various fields. This paper presents ESCoT, an enhanced step-based coordinate trajectory planning method for multiple car-like robots. ESCoT incorporates two key strategies: collaborative...","url_abs":"https://arxiv.org/abs/2508.09581","url_pdf":"https://arxiv.org/pdf/2508.09581v1","authors":"[\"Junkai Jiang\",\"Yihe Chen\",\"Yibin Yang\",\"Ruochen Li\",\"Shaobing Xu\",\"Jianqiang Wang\"]","published":"2025-08-13T07:53:29Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[]","has_code":false}