Visual Navigation Using Sparse Optical Flow and Time-to-Transit

Drawing inspiration from biology, we describe the way in which visual sensing with a monocular camera can provide a reliable signal for navigation of mobile robots. The work takes inspiration from the classic paper [3] which described a behavioral strategy pursued by diving sea birds based on a visual cue called time-to-contact. A closely related concept of time-to-transit, $\tau$, is defined, and it is shown that steering laws based on monocular camera perceptions of $\tau$ can reliably steer a mobile vehicle. The contribution of the paper is two-fold. It provides a simple theory of robust vision-based steering control. It goes on to show how the theory guides the implementation of robust visual navigation using ROS-Gazebo simulations as well as deployment and experiments with a camera-equipped Jackal robot. As will be noted, there is an extensive literature on how animals use optical flow to guide their movements. The novelty of the work below is the introduction of the concepts of Eulerian optical flow and time-to-transit, $\tau$ and the demonstration that control laws based on the $\tau$-values associated with an aggregated set of features in the field of view can be used to reliably steer a laboratory robot.