Reactive and Safety-Aware Path Replanning for Collaborative Applications
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909645578174464 |
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| author | Tonola, Cesare Faroni, Marco Abdolshah, Saeed Hamad, Mazin Haddadin, Sami Pedrocchi, Nicola Beschi, Manuel |
| author_facet | Tonola, Cesare Faroni, Marco Abdolshah, Saeed Hamad, Mazin Haddadin, Sami Pedrocchi, Nicola Beschi, Manuel |
| contents | This paper addresses motion replanning in human-robot collaborative scenarios, emphasizing reactivity and safety-compliant efficiency. While existing human-aware motion planners are effective in structured environments, they often struggle with unpredictable human behavior, leading to safety measures that limit robot performance and throughput. In this study, we combine reactive path replanning and a safety-aware cost function, allowing the robot to adjust its path to changes in the human state. This solution reduces the execution time and the need for trajectory slowdowns without sacrificing safety. Simulations and real-world experiments show the method's effectiveness compared to standard human-robot cooperation approaches, with efficiency enhancements of up to 60\%. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_07192 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Reactive and Safety-Aware Path Replanning for Collaborative Applications Tonola, Cesare Faroni, Marco Abdolshah, Saeed Hamad, Mazin Haddadin, Sami Pedrocchi, Nicola Beschi, Manuel Robotics This paper addresses motion replanning in human-robot collaborative scenarios, emphasizing reactivity and safety-compliant efficiency. While existing human-aware motion planners are effective in structured environments, they often struggle with unpredictable human behavior, leading to safety measures that limit robot performance and throughput. In this study, we combine reactive path replanning and a safety-aware cost function, allowing the robot to adjust its path to changes in the human state. This solution reduces the execution time and the need for trajectory slowdowns without sacrificing safety. Simulations and real-world experiments show the method's effectiveness compared to standard human-robot cooperation approaches, with efficiency enhancements of up to 60\%. |
| title | Reactive and Safety-Aware Path Replanning for Collaborative Applications |
| topic | Robotics |
| url | https://arxiv.org/abs/2503.07192 |