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.Comment: 7 pages, 6 figure