Local terrain mapping for obstacle avoidance using monocular vision

A method for navigation of a small unmanned rotorcraft through an unsurveyed environment using a combination of global positioning system/inertial navigation system (GPS/INS) and a monocular vision system is presented. The environment contains a mix of small, convex obstacles such as tree trunks and large, nonconvex obstacles typical of an urban area. Optical flow measurements obtained from the vision system are fused with measurements of vehicle velocity to compute estimates of range to obstacles. These estimates are used to populate a local occupancy grid, which is fixed to the vehicle. This local occupancy grid allows modeling of complex environments and is suitable for use by generic trajectory planners. Results of simulations in a two-dimensional environment using a potential field obstacle avoidance routine are presented.