OJOp  Vol.2 No.3 , September 2013
Human-Robot Collaborative Planning for Navigation Based on Optimal Control Theory
Author(s) Sousso Kelouwani*
ABSTRACT

Navigation modules are capable of driving a robotic platform without direct human participation. However, for some specific contexts, it is preferable to give the control to a human driver. The human driver participation in the robotic control process when the navigation module is running raises the share control issue. This work presents a new approach for two agents collaborative planning using the optimal control theory and the three-layer architecture. In particular, the problem of a human and a navigation module collaborative planning for a trajectory following is analyzed. The collaborative plan executed by the platform is a weighted summation of each agent control signal. As a result, the proposed architecture could be set to work in autonomous mode, in human direct control mode or in any aggregation of these two operating modes. A collaborative obstacle avoidance maneuver is used to validate this approach. The proposed collaborative architecture could be used for smart wheelchairs, telerobotics and unmanned vehicle applications.


Cite this paper
S. Kelouwani, "Human-Robot Collaborative Planning for Navigation Based on Optimal Control Theory," Open Journal of Optimization, Vol. 2 No. 3, 2013, pp. 72-79. doi: 10.4236/ojop.2013.23010.
References
[1]   M. Pantic, A. Pentland, A. Nijholt and T. S. Huang, “Human Computing and Machine Understanding of Human Behavior: A Survey,” Lecture Notes in Computer Science, 4451 NAI, Hyderabad, 2007, pp. 47-71,

[2]   M. Chatterjee, “Design Research: Building Human-Centered System,” IEEE International Professional Communication Conference (IPCC 2007), Seattle, 1-3 October 2007, pp. 453-458.

[3]   J.-M. Hoc, “Towards a Cognitive Approach to HumanMachine Cooperation in Dynamic Situations,” International Journal of Human Computer Studies, Vol. 54, No. 4, 2001, pp. 509-540.

[4]   S. Krysztof, “Control of a Team of Mobile Robots Based on Non-Ccoperative Equilibra with Partial Coordination,” International Journal Applied Mathematic Computer Science, Vol. 15, No. 1, 2005, pp. 89-97.

[5]   K. Sousso, B. Patrice and C. Paul, “Architecture for Human-Robot Collaborative Navigation,” International Conference on Health Informatics, Valencia, 20 January 2010, pp. 316-323.

[6]   S. Katsura and K. Ohnishi, “Human Cooperative Wheelchair for Haptic Interaction Based on Dual Compliance Control,” IEEE Transactions on Industrial Electronics, Vol. 51, No. 1, 2004, pp. 221-228.

[7]   Z. Qiang, B. Rebsamen, E. Burdet and L. T. Chee, “A Collaborative Wheelchair System,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 16, No. 2, 2008, pp. 161-170.

[8]   C. Urdiales, A. Poncela, I. Sanchez-Tato, F. Galluppi, M. Olivetti and F. Sandoval, “Efficiency Based Reactive Shared Control for Collaborative Human/Robot Navigation,” Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, 29 October-2 November 2007.

[9]   T. Hamagami and H. Hirata, “Development of Intelligent Wheelchair Acquiring Autonomous, Cooperative, and Collaborative Behavior,” IEEE International Conference on Systems, Man and Cybernetics, The Hague, 10-13 October 2004, pp. 3525-3530.

[10]   T. Taha, J. V. Miro and G. Dissanayake, “Wheelchair Driver Assistance and Intention Prediction Using POMDPs,” Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Melbourne, 3-6 December 2007, pp. 449-454. doi:10.1109/ISSNIP.2007.4496885

[11]   Y. Qi, Z. Wang and Y. Huang, “A Non-Contact Eye-Gaze Tracking System for Human Computer Interaction,” Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, Beijing, 2-4 November 2008.

[12]   A. Huntemann, E. Demeester, et al., “Bayesian Plan Recognition and Shared Control under Uncertainty: Assisting Wheelchair Drivers by Tracking Fine Motion Paths,” Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, 29 October-2 November 2007, pp. 3360-3366

[13]   T. Okawa, E. Sato and T. Yamaguchi, “Information Support System with Case-Based Reasoning Using Motion Recognition in Human-Centered City” Proceedings of the SICE Annual Conference, Takamatsu, 17-20 September 2007, pp. 610-613.

[14]   J. B. Cruz Jr., “Leader-Follower Strategies for Multilevel Systems,” IEEE Transactions on Automatic Control, Vol. 23, No. 2, 1978, pp. 244-255. doi:10.1109/TAC.1978.1101716

[15]   M. Simaan and J. B. Cruz Jr., “On the Stackelberg Strategy in Nonzero-Sum Games,” Journal of Optimization Theory and Applications, Vol. 11, No. 5, 1973, pp. 533-555. doi:10.1007/BF00935665

[16]   Y. C. Ho, P. Luh and G. Olsder, “Control-Theoretic View on Incentives,” Automatica, Vol. 18, No. 2, 1982, pp. 167-179. doi:10.1016/0005-1098(82)90106-6

[17]   H. J. Toby, Collett, et al., “Player 2.0: Toward a Practical Robot Programming Framework,” Proceedings of the Australasian Conference on Robotics and Automation (A CRA 2005), Sydney, 5-7 December 2005.

[18]   A. B. Rodney, “A Robust Layered Control System for a Mobile Robot,” IEEE Journal on Robotics and Automation, Vol. 2, 1986, p. 1.

[19]   G. Erann, R. P. Bonnasso, R. Murphy and A. Press, “On Three-Layer Architectures,” Artificial Intelligence and Mobile Robots, 1998, pp. 195-210.

[20]   A. Lankenau, “Avoiding Mode Confusion in Service Robots: The Bremen Autonomous Wheelchair as an Example,” Proceedings of the 7th International Conference on Rehabilitation Robots, Evry, 25-27 April 2001, pp. 162-167.

[21]   S. Carberry, “Techniques for Plan Recognition,” User Modeling and User-Adapted Interaction, Vol. 11, No. 1-2, 2001, pp. 31-48. doi:10.1023/A:1011118925938

[22]   J. Borenstein and Y. Koren, “The Vector Field Histogram-Fast Obstacle Avoidance for Mobilerobots,” IEEE Transactions on Robotics and Automation, Vol. 7, No. 3, 1991, pp. 278-288.

[23]   J. J. Abbott and A. M. Okamura, “Stable Forbidden-Region Virtual Fixtures for Bilateral Telemanipulation,” Transactions of the ASME, Journal of Dynamic Systems, Measurement and Control, Vol. 128, No. 1, 2006, pp. 53-64. doi:10.1115/1.2168163

[24]   A. Astolfi, “Exponential Stabilization of a Wheeled Mobile Robot via Discontinuous Control,” Journal of Dynamic Systems, Measurement, and Control, Vol. 121, No. 1, 1999, pp. 121-126. doi:10.1115/1.2802429

[25]   Y. Kanayama, K. Yoshihiko, F. Miyazaki and T. Noguchi, “A Stable Tracking Control Method for an Autonomous Mobile Robot,” Proceeding of 90 IEEE International Conference Robotics and Automation, Cincinnati, 13-18 May 1990, pp. 384-389. doi:10.1109/ROBOT.1990.126006

[26]   S. Belkhous, A. Azzouzi, M. Saad, C. Nerguizian and V. Nerguizian, “A Novel Approach for Mobile Robot Navigation with Dynamic Obstacles Avoidance,” Journal of Intelligent and Robotic Systems, Vol. 44, 2005, pp. 187-201. doi:10.1007/s10846-005-9010-8

[27]   D. J. Balkcom and M. T. Mason, “Time Optimal Trajectories for Bounded Velocity Differential Drive Vehicles,” International Journal of Robotics Research, Vol. 21, No. 3, 2002, pp. 199-217. doi:10.1177/027836402320556403

 
 
Top