Cognitive vision for autonomous satellite rendezvous and docking

Abstract

We present a cognitively-controlled vision system that combines low-level object recognition and tracking with high-level symbolic reasoning for the purpose of solving difficult space robotics problems—satellite rendezvous and docking. The reasoning module, which encodes a model of the environment, performs deliberation to 1) guide the vision system in a taskdirected manner, 2) activate vision modules depending on the progress of the task, 3) validate the performance of the vision system, and 4) suggest corrections to the vision system when the latter is performing poorly. Reasoning and related elements, among them intention, context, and memory, contribute to improve the performance (i.e., robustness, reliability, and usability). We demonstrate the vision system controlling a robotic arm that autonomously captures a free-flying satellite. Currently such operations are performed either manually or by constructing detailed control scripts. The manual approach is costly and exposes astronauts to danger, while the scripted approach is tedious and error-prone. Therefore, there is substantial interest in performing these operations autonomously, and the work presented here is a step in this direction. To our knowledge, this is the only satellite-capturing system that relies exclusively on vision to estimate the pose of the satellite and can deal with an uncooperative satellite.