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

Authors:
Spencer Ahrens;Daniel Levine;Gregory Andrews;Jonathan P. How
Affiliations:
Aerospace Controls Laboratory, Massachusetts Institute of Technology, Cambridge, MA;Aerospace Controls Laboratory, Massachusetts Institute of Technology, Cambridge, MA;Charles Stark Draper Laboratory, Inc., Cambridge, MA;Aerospace Controls Laboratory, Massachusetts Institute of Technology, Cambridge, MA
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

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Abstract

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 weight-constrained, 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.