A motion-based communication system

For some applications in team robotics, a wireless electronic communication system is not ideal. We propose for some of these tasks that it is more appropriate to communicate through motion, that is by encoding symbols in locomotion and decoding symbols using sensor data. We discuss some of the challenges and requirements of such a system and derive for the LTI case control policies used to enact trajectories that optimize a joint expression of control energy and robustness to observation noise.

[1]  Chee-Yee Chong,et al.  Sensor networks: evolution, opportunities, and challenges , 2003, Proc. IEEE.

[2]  John Baillieul,et al.  Relative Motion of Robots as a Means for Signaling , 2008 .

[3]  Louis J. Lanzerotti,et al.  Solar and Solar Radio Effects on Technologies , 2004 .

[4]  John Baillieul,et al.  The control theory of motion-based communication: Problems in teaching robots to dance , 2012, 2012 American Control Conference (ACC).

[5]  Wenyuan Xu,et al.  The feasibility of launching and detecting jamming attacks in wireless networks , 2005, MobiHoc '05.

[6]  John Baillieul,et al.  Motion based communication channels between mobile robots - A novel paradigm for low bandwidth information exchange , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Erol Sahin,et al.  Swarm Robotics: From Sources of Inspiration to Domains of Application , 2004, Swarm Robotics.

[8]  Antonio Bicchi,et al.  Feedback encoding for efficient symbolic control of dynamical systems , 2006, IEEE Transactions on Automatic Control.

[9]  Scott Niekum,et al.  Learning and generalization of complex tasks from unstructured demonstrations , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  M. Sain Finite dimensional linear systems , 1972 .

[11]  H.Y.D. Yang,et al.  Analysis of RF radiation interference on wireless communication systems , 2003, IEEE Antennas and Wireless Propagation Letters.

[12]  John Baillieul,et al.  Exploiting information content in relative motion , 2009, 2009 American Control Conference.

[13]  P. S. Krishnaprasad,et al.  Steering laws for motion camouflage , 2005, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[14]  Antonio Bicchi,et al.  Towards a Society of Robots , 2010, IEEE Robotics & Automation Magazine.

[15]  P. S. Krishnaprasad,et al.  Equilibria and steering laws for planar formations , 2004, Syst. Control. Lett..

[16]  MengChu Zhou,et al.  Ad-hoc robot wireless communication , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[17]  A. F. T. Winfield,et al.  The application of wireless local area network technology to the control of mobile robots , 2000, Microprocess. Microsystems.

[18]  W.A. Arbaugh Wireless Security Is Different , 2003, Computer.

[19]  Nathan Michael,et al.  Vision-Based, Distributed Control Laws for Motion Coordination of Nonholonomic Robots , 2009, IEEE Transactions on Robotics.

[20]  Robert Bogue,et al.  Microrobots and nanorobots: a review of recent developments , 2010, Ind. Robot.

[21]  P. H. Wells,et al.  An Analysis of the Waggle Dance and Recruitment in Honey Bees , 1967, Physiological Zoology.