Robots operating in close proximity to humans rely heavily on human trust in them to successfully complete their tasks. But what are the real outcomes when this trust is violated? Self-defense law provides a framework for analyzing tangible failure scenarios that can inform the design of robots and their algorithms. Studying self-defense is particularly important for ground robots since they operate within public human environments, where they can pose a legitimate threat to human safety. Moreover, even if ground robots can guarantee human safety, the perception of a threat is enough to warrant human self-defense against robots. In this paper, we synthesize works in law, engineering, and the social sciences to present four actionable recommendations for how the robotics community can craft robots to mitigate the likelihood of self-defense situations arising. We establish how current U.S. self-defense law can justify a human protecting themselves against a robot, discuss the current literature on human attitudes toward robots, and analyze methods that have been produced to allow robots to operate close to humans. Finally, we present hypothetical scenarios that underscore how current robot navigation methods can fail to sufficiently consider self-defense concerns and the need for the recommendations to guide improvements in the field.

翻译：机器人在近距离与人类协作时，其任务完成高度依赖人类对它们的信任。但当这种信任被违背时，实际后果会是什么？正当防卫法为分析具体的故障场景提供了框架，可指导机器人及其算法的设计。对于地面机器人而言，研究正当防卫尤为重要——它们活动于公共人类环境中，可能对人类安全构成真实威胁。此外，即使地面机器人能确保物理安全，威胁感知本身也足以引发人类对机器人的正当防卫。本文综合借鉴法律、工程学和社会科学领域的研究成果，提出四项可行建议，指导机器人社区如何构建能降低正当防卫情境发生概率的机器人系统。我们阐明了美国现行正当防卫法如何支持人类针对机器人实施自卫，梳理了当前关于人类对机器人态度的文献，并分析了现有让机器人近距离接触人类的操作方法。最后通过假设性场景，揭示当前机器人导航方法未能充分考量正当防卫问题的现状，以及亟需以这些建议指导领域改进的必要性。