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 e...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers
2010
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| Online Access: | http://hdl.handle.net/1721.1/53520 https://orcid.org/0000-0001-8576-1930 |
| Summary: | 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. |
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