Vision-based guidance and control of a hovering vehicle in unknown, GPS-denied environments

— This paper describes the system architecture and core algorithms for a quadrotor helicopter that uses vision data to navigate an unknown, indoor, GPS-denied environment. Without external sensing, an estimation system that relies only on integrating inertial data will have rapidly drifting position estimates. Micro aerial vehicles (MAVs) are stringently weightconstrained, leaving little margin for additional sensors beyond the mission payload. The approach taken in this paper is to introduce an architecture that exploits a common mission payload, namely a video camera, as a dual-use sensor to aid in navigation. Several core algorithms, including a fast environment mapper and a novel heuristic for obstacle avoidance, are also presented. Finally, drift-free hover and obstacle avoidance flight tests in a controlled environment are presented and analyzed.

• Type: Conference
• Year: 2009
• Where: ICRA
• Authors: Spencer Ahrens, Daniel Levine, Gregory Andrews, Jonathan P. How
• Keywords: Core Algorithms, ICRA 2009, Mission Payload, Obstacle Avoidance, Robotics