让机器人通过共识与涡旋场实现更自然的社交导航
Socially-Aware Opinion-Based Navigation with Oval Limit Cycles
- 用意见动态达成路径共识，结合涡旋场生成社交可接受轨迹
- 联合方法在实验中显著优于单独使用任一技术
- 适合需要与人共处的移动机器人系统研究者参考
当人类在共享空间中移动时，会选择既保障彼此安全又尽量减少路径调整的导航策略。他们通过非语言交流达成运动方向的共识，并以相互可接受的方式执行。社交感知导航旨在将这一逻辑复制到机器人中。现有工作或关注机器人如何与人类协商，或如何实现社会可接受的移动。本文提出一种整体性方法，同时考虑这两个方面：通过结合意见动态（达成共识）与涡旋场（生成社交可接受轨迹），结果优于单独使用任一技术。该方法提升了机器人在人群中的自然性和安全性。
原文摘要 · Abstract (English)
When humans move in a shared space, they choose navigation strategies that preserve their mutual safety. At the same time, each human seeks to minimise the number of modifications to her/his path. In order to achieve this result, humans use unwritten rules and reach a consensus on their decisions about the motion direction by exchanging non-verbal messages. They then implement their choice in a mutually acceptable way. Socially-aware navigation denotes a research effort aimed at replicating this logic inside robots. Existing results focus either on how robots can participate in negotiations with humans, or on how they can move in a socially acceptable way. We propose a holistic approach in which the two aspects are jointly considered. Specifically, we show that by combining opinion dynamics (to reach a consensus) with vortex fields (to generate socially acceptable trajectories), the result outperforms the application of the two techniques in isolation.
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