A Modular Framework for Flexible Planning in Human-Robot Collaboration
<|reference_start|>A Modular Framework for Flexible Planning in Human-Robot Collaboration: 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.<|reference_end|>
@article{belcamino2024a,
    title={A Modular Framework for Flexible Planning in Human-Robot Collaboration},
    author={Valerio Belcamino, Mariya Kilina, Linda Lastrico, Alessandro Carf`i
  and Fulvio Mastrogiovanni},
    journal={arXiv preprint arXiv:2406.04907},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.04907},
    primaryClass={cs.RO cs.HC}
}