arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2402.04768cs.ROcs.CVcs.HC
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基于社会运动预测的人机交互机器人交互行为生成

Robot Interaction Behavior Generation based on Social Motion Forecasting for Human-Robot Interaction

Technische Universität Wien (TU Wien)(维也纳技术大学);German Aerospace Center(德国航空航天中心)

Esteve Valls Mascaro, Yashuai Yan, Dongheui Lee

AI总结:

提出共享人-机器人表示空间中的 ECHO 模型,通过基于周围智能体细化个体运动实现社会运动预测,并据此生成可由文本控制的实时人机交互行为。

摘要:

将机器人融入有人环境是一项复杂挑战,需要理解人类社会动态。在本工作中,我们提出在共享的人-机器人表示空间中对社会运动预测进行建模,这使我们能够合成在社会场景中与人类互动的机器人运动,尽管在运动训练中没有观察到任何机器人。我们开发了一种名为 ECHO 的基于 transformer 的架构,它在上述共享空间中运行,以预测在社会场景中遇到的智能体的未来运动。与先前工作不同,我们将社会运动问题重新表述为基于周围智能体对预测的个体运动进行细化,这促进了训练,同时当场景中只有一个人时允许进行单一运动预测。我们在多人和人-机器人运动预测任务中评估了我们的模型,并以大幅优势获得了最先进的性能,同时保持高效并实时运行。此外,我们的定性结果展示了我们的方法在生成可通过文本命令控制的人机交互行为方面的有效性。网页:https://evm7.github.io/ECHO/

英文摘要:

Integrating robots into populated environments is a complex challenge that requires an understanding of human social dynamics. In this work, we propose to model social motion forecasting in a shared human-robot representation space, which facilitates us to synthesize robot motions that interact with humans in social scenarios despite not observing any robot in the motion training. We develop a transformer-based architecture called ECHO, which operates in the aforementioned shared space to predict the future motions of the agents encountered in social scenarios. Contrary to prior works, we reformulate the social motion problem as the refinement of the predicted individual motions based on the surrounding agents, which facilitates the training while allowing for single-motion forecasting when only one human is in the scene. We evaluate our model in multi-person and human-robot motion forecasting tasks and obtain state-of-the-art performance by a large margin while being efficient and performing in real-time. Additionally, our qualitative results showcase the effectiveness of our approach in generating human-robot interaction behaviors that can be controlled via text commands. Webpage: https://evm7.github.io/ECHO/

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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