EMPOWER: Embodied Multi-role Open-vocabulary Planning with Online Grounding and Execution
<|reference_start|>EMPOWER: Embodied Multi-role Open-vocabulary Planning with Online Grounding and Execution: Task planning for robots in real-life settings presents significant challenges. These challenges stem from three primary issues: the difficulty in identifying grounded sequences of steps to achieve a goal; the lack of a standardized mapping between high-level actions and low-level commands; and the challenge of maintaining low computational overhead given the limited resources of robotic hardware. We introduce EMPOWER, a framework designed for open-vocabulary online grounding and planning for embodied agents aimed at addressing these issues. By leveraging efficient pre-trained foundation models and a multi-role mechanism, EMPOWER demonstrates notable improvements in grounded planning and execution. Quantitative results highlight the effectiveness of our approach, achieving an average success rate of 0.73 across six different real-life scenarios using a TIAGo robot.<|reference_end|>
@article{argenziano2024empower:,
    title={EMPOWER: Embodied Multi-role Open-vocabulary Planning with Online
  Grounding and Execution},
    author={Francesco Argenziano, Michele Brienza, Vincenzo Suriani, Daniele
  Nardi, Domenico D. Bloisi},
    journal={arXiv preprint arXiv:2408.17379},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.17379},
    primaryClass={cs.RO cs.AI}
}