Vision is a popular and effective sensor for robotics from which we can derive rich information about the environment: the geometry and semantics of the scene, as well as the age, gender, identity, activity and even emotional state of humans within that scene. This raises important questions about the reach, lifespan, and potential misuse of this information. This paper is a call to action to consider privacy in the context of robotic vision. We propose a specific form privacy preservation in which no images are captured or could be reconstructed by an attacker even with full remote access. We present a set of principles by which such systems can be designed, and through a case study in localisation demonstrate in simulation a specific implementation that delivers an important robotic capability in an inherently privacy-preserving manner. This is a first step, and we hope to inspire future works that expand the range of applications open to sighted robotic systems.

翻译：视觉是机器人技术中常用且有效的传感器，可从中获取关于环境的丰富信息：场景的几何与语义，以及场景中人类的年龄、性别、身份、活动甚至情绪状态。这引发了关于这些信息获取范围、生命周期及潜在滥用的重要问题。本文旨在呼吁在机器人视觉背景下考虑隐私保护。我们提出了一种特定形式的隐私保护，即不捕获任何图像，且即使攻击者拥有完全远程访问权限也无法重建图像。我们提出了一套设计此类系统的原则，并通过一个定位案例研究，在仿真中演示了以固有隐私保护方式实现重要机器人能力的具体实施方案。这是初步探索，我们希望激发未来研究，拓宽具视觉能力的机器人系统的应用范围。