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Motion planning for a rapid mobile manipulator using model-based ZMP stabilization

Published online by Cambridge University Press:  05 November 2014

Dongil Choi  and
Jun-ho Oh
Dongil Choi*
Affiliation:
The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA
Jun-ho Oh*
Affiliation:
HUBO Laboratory (Humanoid Robot Research Center), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
*
*Corresponding authors. E-mails: doyle.choi.cdi@gmail.com, jhoh@kaist.ac.kr
*Corresponding authors. E-mails: doyle.choi.cdi@gmail.com, jhoh@kaist.ac.kr
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Summary

This paper introduces a novel approach to motion planning for a rapid mobile manipulator using inverted pendulum models. Our aim was to realize an actual rapid mobile manipulator with high acceleration and speed performance for an object's delivery. In our research, we developed an actual rapid mobile manipulator called KDMR-1. We proposed simple motion planning methods using a single inverted pendulum model (SIPM) and a double inverted pendulum model (DIPM), which are easily adaptable to a real-time system with only a small computational burden. The SIPM was useful for basic movement but did not provide object carrying capability. For that, a DIPM was proposed. In both models, we designed linear quadratic optimal controllers to stabilize the Zero Moment Point (ZMP). Two kinds of ZMP stabilization strategies were proposed, fixed ZMP and relaxed ZMP. Using these strategies, we realized optimal ZMP stabilizations for a real-time rapid mobile manipulator. For decoupled forward and rotational linear DIPM, we designed a centrifugal acceleration compensation model in the manner of feedback linearization. The experimental results showed high acceleration and speed performances during rapid object delivery.

Keywords

Wheeled robotsService robotsManipulation planning
Type
Articles
Information
Robotica , Volume 32 , Issue 6 , September 2014 , E2
Copyright
Copyright © Cambridge University Press 2014 

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References

1. Dubowsky, S. and Vance, E. E., “Planning Mobile Manipulator Motions Considering Vehicle Dynamic Stability Constraints,” Proceedings of the IEEE International Conference on Robotics and Automation, Scottsdale, AZ, USA, (1989) pp. 1271–1276.Google Scholar
2. Fukuda, T. and Fujisawa, Y., “Manipulator/Vehicle System for Man-Robot Cooperation,” Proceedings of the IEEE International Conference on Robotics and Automation, Nice, France, (1992) pp. 74–79.Google Scholar
3. Huang, Q., Tanie, K. and Sugano, S., “Coordinated motion planning for a mobile manipulator considering stability and manipulation,” Int. J. Robot. Res. 19 (8), 732–742 (2000).Google Scholar
4. Kim, J. and Chung, W. K., “Real-time zero moment point compensation method using null motion for mobile manipulators,” Adv. Robot. 20 (5), 581–593 (2006).Google Scholar
5. Papadopoulos, E. and Rey, D. A., “The force-angle measure of tipover stability margin for mobile manipulators,” Veh. Syst. Dyn. 33 (1), 29–48 (2000).CrossRefGoogle Scholar
6. Moosavian, S. A. A. and Alipour, K., “Tip-Over Stability of Suspended Wheeled Mobile Robots,” Proceedings of the IEEE International Conference on Mechatronics and Automation, Harbin, P.R. China, (2007) pp. 1356–1361.Google Scholar
7. Lee, S., Leibold, M., Buss, M. and Park, F. C., “Online Stability Compensation of Mobile Manipulators Using Recursive Calculation of ZMP Gradients,” Proceedings of the IEEE International Conference on Robotics and Automation, Saint Paul, Minnesota, USA, (2012) pp. 850–855.Google Scholar
8. Kim, J., Chung, W. K., Youm, Y. and Lee, B. H., “Real-time ZMP Compensation Method using Null Motion for Mobile Manipulators,” Proceedings of the IEEE International Conference on Robotics and Automation, Washington, DC, USA, (2002) pp. 1967–1972.Google Scholar
9. Kim, M., Choi, D. and Oh, J.-H., “Stabilization of a Rapid Four-wheeled Mobile Platform Using the ZMP Stabilization Method,” Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Montreal, Canada, (2010) pp. 317–322.Google Scholar
10. Choi, D., Kim, M. and Oh, J. H., “Development of a rapid mobile robot with a multi-degree-of-freedom inverted pendulum using the model-based zero-moment point stabilization method,” Adv. Robot. 26 (5–6), 515–535 (2012).Google Scholar
11. Choi, D. and Oh, J., “ZMP Stabilization of Rapid Mobile Manipulator,” Proceedings of the IEEE International Conference on Robotics and Automation, St. paul, USA, (2012) pp. 883–888.Google Scholar
12. Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., K. Yokoi and Hirukawa, H., “Biped Walking Pattern Generation by using Preview Control of Zero-Moment Point,” Proceedings of the IEEE International Conference on Robotics and Automation, Taipei, Taiwan, (2003) pp. 1620–1626.Google Scholar
13. Sugihara, T., Nakamura, Y. h. and Inoue, H., “Realtime Humanoid Motion Generat ion through ZMP Manipulation based on Inverted Pendulum Control,” Proceedings of the IEEE International Conference on Robotics and Automation, Washington, DC, USA, (2002) pp. 1404–1409.Google Scholar
14. Park, I.-W., Kim, J.-Y. and Oh, J.-H., “Online walking pattern generation and its application to a biped humanoid robot — KHR-3 (HUBO),” Adv. Robot. 22 (2), 159–190 (2008).Google Scholar
15. Choi, D., “Development of a Rapid Mobile Manipulator and Model-based Stabilization Methods,” Proceedings of the Mechanical Engineering, KAIST, Daejeon, (2012).Google Scholar
16. Vukobratovic, M. and Borovac, B., “Zero-moment point — thirty five years of its life,” Int. J. Humanoid Robot. 1 (1), 157–173 (2004).Google Scholar
17. Sugano, S., Huang, Q. and Kato, I., “Stability Criteria in Controlling Mobile Robotics Systems,” Proceedings of the IEEE International Conference on Intelligent Robots and Systems, Tokyo, Japan, (1993) pp. 832–838.Google Scholar
18. Napoleon, S. Nakaura and Sampei, M., “Balance Control Analysis of Humanoid Robot based on ZMP Feedback Control,” Proceedings of the IEEE International Conference on Intelligent Robots and Systems, EPFL. Lausanne, Switzerland, (2002) pp. 2437–2442.Google Scholar
19. Choi, D. and Oh, J.-h., “Development of cartesian arm exoskeleton system (CAES) using 3-axis force/torque sensor,” Int. J. Control, Autom. Syst. 11 (5), 976–983 (2013).Google Scholar
20. Choi, D. and Oh, J.-H., “Four and Two Wheel Transformable Dynamic Mobile Platform,” Proceedings of the IEEE International Conference on Robotics and Automation, Shanghai, P.R. China, (2011) pp. 1–4.Google Scholar
21. Choi, D. and Oh, J.-H., “Human-Friendly Motion Control of a Wheeled Inverted Pendulum by Reduced-Order Disturbance Observer,” Proceedings of the IEEE International Conference on Robotics and Automation, Pasadena, USA, (2008) pp. 2521–2526.Google Scholar
22. Choi, D. and Oh, J.-H., “Active Suspension for a Rapid Mobile Robot Using Cartesian Computed Torque Control,” in Journal of Intelligent and Robotic Systems, published in Online First, (2014).Google Scholar