Distributed Motion Estimation of Space Objects Using Dual Quaternions

This paper examines the motion estimation problem for space objects using multiple image sensors in a connected network. The objective is to increase the estimation precision of relative translational and rotational motions based on integrated dual quaternion representations and cooperation between connected sensors. The relative motion of space objects is rst formulated using dual elements to express its kinematics and dynamics. Two modular optimization approaches, namely dual decomposition and distributed Newton methods, for decomposing this cooperative estimation problem among the sensors is then proposed. Simulation results from single sensor estimation and two distributed estimation frameworks are provided and compared.

[1]  Magnus Egerstedt,et al.  Graph Theoretic Methods in Multiagent Networks , 2010, Princeton Series in Applied Mathematics.

[2]  Anders Robertsson,et al.  Visual position tracking using dual quaternions with hand-eye motion constraints , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[3]  Fan-Ren Chang,et al.  Estimation of relative orientation using dual quaternion , 2010, 2010 International Conference on System Science and Engineering.

[4]  M. Mesbahi,et al.  DISTRIBUTED ORBIT DETERMINATION VIA ESTIMATION CONSENSUS , 2011 .

[5]  Stephen P. Boyd,et al.  Distributed large scale network utility maximization , 2009, 2009 IEEE International Symposium on Information Theory.

[6]  J. S. Goddarda,et al.  Pose and Motion Estimation Using Dual Quaternion-Based Extended Kalman Filtering , 2008 .

[7]  Angelo M. Sabatini,et al.  Quaternion-based extended Kalman filter for determining orientation by inertial and magnetic sensing , 2006, IEEE Transactions on Biomedical Engineering.

[8]  Robert B. McGhee,et al.  An extended Kalman filter for quaternion-based orientation estimation using MARG sensors , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[9]  Mongi A. Abidi,et al.  Pose and motion estimation using dual quaternion-based extended Kalman filtering , 1998, Electronic Imaging.

[10]  S. Grime,et al.  Data fusion in decentralized sensor networks , 1994 .

[11]  Asuman E. Ozdaglar,et al.  A distributed Newton method for Network Utility Maximization , 2010, 49th IEEE Conference on Decision and Control (CDC).

[12]  C. Barus.  A treatise on the theory of screws , 1998 .

[13]  William Rowan Hamilton,et al.  ON QUATERNIONS, OR ON A NEW SYSTEM OF IMAGINARIES IN ALGEBRA , 1847 .

[14]  Stephen J. Wright,et al.  Primal-Dual Interior-Point Methods , 1997 .

[15]  Jiang Wang,et al.  3D relative position and orientation estimation using Kalman filter for robot control , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[16]  Stephen P. Boyd,et al.  Distributed estimation via dual decomposition , 2007, 2007 European Control Conference (ECC).

[17]  Nikos Komodakis,et al.  MRF Optimization via Dual Decomposition: Message-Passing Revisited , 2007, 2007 IEEE 11th International Conference on Computer Vision.