Human-centered In-building Embodied Delivery Benchmark
<|reference_start|>Human-centered In-building Embodied Delivery Benchmark: Recently, the concept of embodied intelligence has been widely accepted and popularized, leading people to naturally consider the potential for commercialization in this field. In this work, we propose a specific commercial scenario simulation, human-centered in-building embodied delivery. Furthermore, for this scenario, we have developed a brand-new virtual environment system from scratch, constructing a multi-level connected building space modeled after a polar research station. This environment also includes autonomous human characters and robots with grasping and mobility capabilities, as well as a large number of interactive items. Based on this environment, we have built a delivery dataset containing 13k language instructions to guide robots in providing services. We simulate human behavior through human characters and sample their various needs in daily life. Finally, we proposed a method centered around a large multimodal model to serve as the baseline system for this dataset. Compared to past embodied data work, our work focuses on a virtual environment centered around human-robot interaction for commercial scenarios. We believe this will bring new perspectives and exploration angles to the embodied community.<|reference_end|>
@article{xu2024human-centered,
    title={Human-centered In-building Embodied Delivery Benchmark},
    author={Zhuoqun Xu, Yang Liu, Xiaoqi Li, Jiyao Zhang, and Hao Dong},
    journal={arXiv preprint arXiv:2406.17898},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.17898},
    primaryClass={cs.RO cs.AI}
}