  Reliable operation in inclement weather is essential to the deployment of
safe autonomous vehicles (AVs). Robustness and reliability can be achieved by
fusing data from the standard AV sensor suite (i.e., lidars, cameras) with
weather robust sensors, such as millimetre-wavelength radar. Critically,
accurate sensor data fusion requires knowledge of the rigid-body transform
between sensor pairs, which can be determined through the process of extrinsic
calibration. A number of extrinsic calibration algorithms have been designed
for 2D (planar) radar sensors - however, recently-developed, low-cost 3D
millimetre-wavelength radars are set to displace their 2D counterparts in many
applications. In this paper, we present a continuous-time 3D radar-to-camera
extrinsic calibration algorithm that utilizes radar velocity measurements and,
unlike the majority of existing techniques, does not require specialized radar
retroreflectors to be present in the environment. We derive the observability
properties of our formulation and demonstrate the efficacy of our algorithm
through synthetic and real-world experiments.
