Mapping and path planning in complex environments: An obstacle avoidance approach for an unmanned helicopter

Abstract

This paper presents an obstacle avoidance method that is performed with an unmanned helicopter. The approach begins with a mapping step where information from sensor data about previously unknown dangers is extracted into an occupancy grid and eventually converted into a polygonal 3D world model. This continuously updating map is used by a path planner that generates and updates a 3D trajectory guiding the vehicle through safe passages around the detected objects. The algorithms are generic but optimized for unmanned aircraft and a stereo camera as the environmental sensor. Computation is fully executed on board so that a ground control station is only needed for supervision. With successful obstacle detection and avoidance flight tests, the paper shows the qualification of the presented method under real operational conditions.