Pose estimation of non-cooperative targets without feature tracking

Pose estimation is playing the vital role in the final approach phase of two spacecraft, one is the target spacecraft and the other one is the observation spacecraft. Traditional techniques are usually based on feature tracking, which will not work when sufficient features are unavailable. To deal with this problem, we present a stereo camera-based pose estimation method without feature tracking. First, stereo vision is used to reconstruct 2.5D of the target spacecraft and a 3D reconstruction is presented by merged all the point cloud of each viewpoint. Then a target-coordinate system is built using the reconstruction results. Finally, point cloud registration algorithm is used to solve the current pose between the observation spacecraft and the target spacecraft. Experimental results show that both the position errors and the attitude errors satisfy the requirements of pose estimation. The method provides a solution for pose estimation without knowing the information of the targets and this algorithm is with wider application range compared with the other algorithms based on feature tracking.

[1]  Simone D'Amico,et al.  Prisma Formation Flying Demonstrator: Overview and Conclusions from the Nominal Mission , 2012 .

[2]  Jonathan P. How,et al.  Formation sensing and control technologies for a separated spacecraft interferometer , 1998, Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207).

[3]  朱枫,et al.  Pose estimation of non-cooperative spacecraft based on collaboration of space-ground and rectangle feature , 2011 .

[4]  Paul J. Besl,et al.  Method for registration of 3-D shapes , 1992, Other Conferences.

[5]  Jonathan P. How,et al.  Spacecraft Formation Flying: Dynamics, Control and Navigation , 2009 .

[6]  Xinhua Zhuang,et al.  Pose estimation from corresponding point data , 1989, IEEE Trans. Syst. Man Cybern..

[7]  Fuyuto Terui MODEL BASED VISUAL RELATIVE MOTION ESTIMATION AND CONTROL OF A SPACECRAFT UTILIZING COMPUTER , 2009 .

[8]  Alin Albu-Schäffer,et al.  Robotic On-Orbit Servicing - DLR's Experience and Perspective , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Shai Segal,et al.  Vision-based relative state estimation of non-cooperative spacecraft under modeling uncertainty , 2011, 2011 Aerospace Conference.

[10]  Gregory D. Hager,et al.  Fast and Globally Convergent Pose Estimation from Video Images , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Robert B. Friend,et al.  Orbital Express program summary and mission overview , 2008, SPIE Defense + Commercial Sensing.

[12]  Farhad Aghili,et al.  An adaptive vision system for guidance of a robotic manipulator to capture a tumbling satellite with unknown dynamics , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.