Robots operating in close proximity to humans rely heavily on human trust 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 environments, where they can pose a legitimate threat to the safety of nearby humans. Moreover, even if ground robots can guarantee human safety, the perception of a physical threat is sufficient to justify human self-defense against robots. In this paper, we synthesize works in law, engineering, and social science 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：在人类附近运行的机器人高度依赖人类信任才能成功完成任务。但当这种信任被违背时，实际后果是什么？自卫法为分析具体的失败场景提供了一个框架，可用于指导机器人及其算法的设计。研究自卫问题对于地面机器人尤为重要，因为它们在公共环境中运行，可能对附近人类的安全构成实际威胁。此外，即使地面机器人能够保证人类安全，对人类身体威胁的感知也足以证明人对机器人实施自卫的合理性。在本文中，我们综合法学、工程学和社会科学领域的成果，提出四项可操作建议，指导机器人社区如何设计机器人以降低自卫情况发生的可能性。我们明确了美国现行自卫法如何证明人类保护自己免受机器人伤害的合理性，讨论了当前关于人类对机器人态度的文献，并分析了允许机器人在人类附近运行的方法。最后，我们提出假设性场景，强调当前机器人导航方法在充分考虑自卫关切方面的不足，以及通过建议指导该领域改进的必要性。