A Modular Framework for Flexible Planning in Human-Robot Collaboration
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866929377288126464 |
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| author | Belcamino, Valerio Kilina, Mariya Lastrico, Linda Carfì, Alessandro Mastrogiovanni, Fulvio |
| author_facet | Belcamino, Valerio Kilina, Mariya Lastrico, Linda Carfì, Alessandro Mastrogiovanni, Fulvio |
| contents | This paper presents a comprehensive framework to enhance Human-Robot Collaboration (HRC) in real-world scenarios. It introduces a formalism to model articulated tasks, requiring cooperation between two agents, through a smaller set of primitives. Our implementation leverages Hierarchical Task Networks (HTN) planning and a modular multisensory perception pipeline, which includes vision, human activity recognition, and tactile sensing. To showcase the system's scalability, we present an experimental scenario where two humans alternate in collaborating with a Baxter robot to assemble four pieces of furniture with variable components. This integration highlights promising advancements in HRC, suggesting a scalable approach for complex, cooperative tasks across diverse applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_04907 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Modular Framework for Flexible Planning in Human-Robot Collaboration Belcamino, Valerio Kilina, Mariya Lastrico, Linda Carfì, Alessandro Mastrogiovanni, Fulvio Robotics Human-Computer Interaction This paper presents a comprehensive framework to enhance Human-Robot Collaboration (HRC) in real-world scenarios. It introduces a formalism to model articulated tasks, requiring cooperation between two agents, through a smaller set of primitives. Our implementation leverages Hierarchical Task Networks (HTN) planning and a modular multisensory perception pipeline, which includes vision, human activity recognition, and tactile sensing. To showcase the system's scalability, we present an experimental scenario where two humans alternate in collaborating with a Baxter robot to assemble four pieces of furniture with variable components. This integration highlights promising advancements in HRC, suggesting a scalable approach for complex, cooperative tasks across diverse applications. |
| title | A Modular Framework for Flexible Planning in Human-Robot Collaboration |
| topic | Robotics Human-Computer Interaction |
| url | https://arxiv.org/abs/2406.04907 |