Comparison of Temporal Filters for Optical Flow Estimation in Continuous Mobile Robot Navigation

We present our complete study involving comparisons of three spatio-temporal filters used in the estimation of optical flow for continuous mobile robot navigation. Previous comparisons of optical flow and associated techniques have compared performance in terms of accuracy and/or efficiency, and only in isolation. These comparisons are inadequate for addressing applicability to continuous, real-time operation as part of a robot control loop. In recent work [11], we presented a comparison of optical flow techniques for corridor navigation through two biologically inspired behaviours: corridor centring and visual odometry. In that study, flow was predominantly constant. In this paper we give new results from comparisons for flow-divergence based docking, where flow is non-constant. Results for traditionally used Gaussian filters indicate that long latencies significantly impede performance for real-time tasks in the control loop.