Local Terrain Mapping for Obstacle Avoidance using Monocular Vision

We present a method for navigation of a small unmanned rotorcraft through an unsurveyed environment consisting of forest and urban canyons. Optical flow measurements obtained from a 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.