Vision-aided inertial navigation for pinpoint planetary landing |
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| Institution: | 1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;2. Deep Space Exploration Research Center, Harbin Institute of Technology, Harbin 150001, China;1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;2. Advanced Space Concepts Laboratory, University of Strathclyde, Glasgow G1 1XJ, United Kingdom;3. Shanghai Engineering Center for Microsatellites, Shanghai 201203, China;1. Aerospace Flight Dynamics Laboratory, Beijing Aerospace Control Center, Beijing 100094, China;2. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;3. Department of Spacecraft Management, Beijing Aerospace Control Center, Beijing 100094, China;4. Chinese Academy of Sciences, Beijing 100101, China;1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China;2. Advanced Space Technology Laboratory, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China;1. University of Tokyo, 7-3-1 Hongō, Bunkyō-ku, Tōkyō-to 113-8654, Japan;2. Institute of Space and Astronautical Science/Japan Aerospace Exploration Agency, 3-1-1, Yoshinodai, Chuo-ku, Sagamihara City, Kanagawa Prefecture 252-5210, Japan;3. Earth Life Science Institute, 2-12-1-IE-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan;1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China;2. Advanced Space Technology Laboratory, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China |
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| Abstract: | Autonomous and safe landing spacecraft on moon and planetary bodies is a rather difficult and risky task. Accurate relative navigation between the spacecraft and the planetary surface is essential, together with the autonomous hazard detection and avoidance. This paper describes the vision-aided inertial navigation (VAIN) scheme to meet the pinpoint landing requirement of the next generation planetary lander. Images of distinctive surface feature called feature points/landmarks are detected and tracked autonomously to improve the performance of inertial navigation. Landmark image information derived from optical navigation camera and the spacecraft state information sensed by IMU (Inertial Measurement Unit) are integrated in extended Kalman filter algorithm. The validity of the proposed navigation scheme is confirmed by computer simulation. |
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