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A new approach on human–robot collaboration with humanoid robot RH-2

Published online by Cambridge University Press:  18 March 2011

C. A. Monje ,
P. Pierro  and
C. Balaguer
C. A. Monje*
Affiliation:
Department of Systems Engineering and Automatics, University Carlos III of Madrid, Madrid, 28911/Leganés, Spain
P. Pierro
Affiliation:
Department of Systems Engineering and Automatics, University Carlos III of Madrid, Madrid, 28911/Leganés, Spain
C. Balaguer
Affiliation:
Department of Systems Engineering and Automatics, University Carlos III of Madrid, Madrid, 28911/Leganés, Spain
*
*Corresponding author. E-mail: [email protected]
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Summary

This paper presents a novel control architecture for humanoid robot RH-2. The main objective is that a robot can perform different tasks in collaboration with humans in working environments. In order to achieve this goal, two control loops have to be defined. The outer loop, called collaborative control loop, is devoted to the generation of stable motion patterns for a robot, given a specific manipulation task. The inner loop, called posture stability control loop, acts to guarantee the stability of humanoid for different poses determined by motion patterns. A case study is presented in order to show the effectiveness of the proposed control architecture.

Keywords

Humanoid robot RH-2Human–robot collaborationControl architectureKinematic modelDynamic model
Type
Articles
Information
Robotica , Volume 29 , Issue 6 , October 2011 , pp. 949 - 957
Copyright
Copyright © Cambridge University Press 2011

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References

1.Green, S. A., Billinghurst, M., Chen, X. and Chase, J. G., “Human-robot collaboration: A literature review and augmented reality approach in design,” Int. J. Adv. Robot. Syst. 5 (1), 1–18 (2008).CrossRefGoogle Scholar
2.Pierro, P., Monje, C. A. and Balaguer, C., “Modelling and Control of the Humanoid Robot RH-1 for Collaborative Tasks,” Proceedings of IEEE RAS/RSJ Conference on Humanoids Robots, Daejeon, Korea (2008) pp. 125–131.Google Scholar
3.Yamamoto, Y., Eda, H. and Yun, X., “Coordinated Task Execution of a Human and a Mobile Manipulator,” Proceedings of IEEE International Conference on Robotics and Automation, Vol. 2 (1996), pp. 1006–1011.Google Scholar
4.Khatib, O., Sentis, L., Park, J. and Warren, J., “Whole-body dynamic behavior and control of human-like robots,” Int. J. Human. Robot. 1, 29–43 (2004).CrossRefGoogle Scholar
5.Sentis, L. and Khatib, O., “Synthesis of whole-body behaviors through hierarchical control of behavioral primitives,” Int. J. Human. Robot. 2 (4), 505–518 (2005).CrossRefGoogle Scholar
6.Hinds, P. J., Roberts, T. L. and Jones, H., “Whose job is it anyway? A study of human-robot interaction in a collaborative task,” Human-Comput. Interact. 19, 151–181 (2004).CrossRefGoogle Scholar
7.Nakamura, Y. and Hanafusa, H., “Optimal redundancy control of robot manipulators,” Int. J. Robot. Res. 6 (1), 32–42 (1986).CrossRefGoogle Scholar
8.Gienger, M., Janen, H. and Goerick, C., “Task-Oriented Whole Body Motion for Humanoid Robots,” Proceedings of IEEE International Conference on Humanoid Robots (Humanoids2005), Los Angeles, USA (2005) pp. 238–244.CrossRefGoogle Scholar
9.Sian, N. E., Yokoi, K., Kajita, S., Kanehiro, F. and Tanie, K., “A switching command-based whole-body operation method for humanoid robots,” IEEE/ASME Trans. Mechatron. 10 (5), 546–559 (2005).Google Scholar
10.Khatib, O., “A unified approach for motion and force control of robot manipulators: The operational space formulation,” Int. J. Robot. Res. 3 (1), 43–53 (1987).Google Scholar
11.Samson, C., Le Borgne, M. and Espiau, B., Robot Control: the Task Function Approach Clarendon Press, Oxford, UK, 1991).Google Scholar
12.Siciliano, B. and Slotine, J.-J., “A General Framework for Managing Multiple Tasks in Highly Redundant Robotic Systems,” Proceedings of IEEE International Conference on Advanced Robotics (ICAR'91), Pisa, Italy (2003) pp. 1211–1216.Google Scholar
13.Siciliano, B., Sciavicco, L., Villani, L. and Oriolo, G., eds., Robotics: Modelling, Planning and Control Springer, New York, NY, 2009).CrossRefGoogle Scholar
14.Kajita, S. and Tani, K., “Study of Dynamic Biped Locomotion on Rugged Terrain,” Proceedings of IEEE International Conference on Robotics and Automation (ICRA) (1991) pp. 1405–1411.Google Scholar
15.Kajita, S., Kanehiro, F., Kaneko, K., Yokoi, K. and Hirukawa, H., “The 3D Linear Inverted Pendulum Mode: A Simple Modeling for a Biped Walking Pattern Generator,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Maui, Hawaii (2001) pp. 239–246.Google Scholar
16.Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K. and Hirukawa, H., “Biped Walking Pattern Generation by Using Preview Control of Zero-Moment Point,” Proceedings of IEEE International Conference on Robotics and Automation (ICRA), Taipei, Taiwan (2003) pp. 1620–1626.Google Scholar
17.Sugihara, T. and Nakamura, Y., “Variable Impedant Inverted Pendulum Model Control for a Seamless Contact Phase Transition on Humanoid Robot,” Proceedings of IEEE International Conference on Humanoid Robots (Humanoids 2003), Germany (2003).Google Scholar
18.Altendorfer, R., Saranli, U., Komsuoglu, H., Koditschek, D. E., Benjamin Brown, H., Buehler, M., Moore, N., McMordie, D. and Full, R., “Evidence for Spring Loaded Inverted Pendulum Running in a Hexapod Robot,” In: Experimental Robotics VII (Rus, D. and Singh, S., eds.) (Springer-Verlag, New York, NY, 2009) pp. 291–302.Google Scholar
19.Komura, T., Leung, H., Kudoh, S. and Kuffner, J., “A Feedback Controller for Biped Humanoids that Can Counteract Large Perturbations During Gait,” Proceedings of IEEE International Conference on Robotics and Automation (ICRA), Barcelona, Spain, (2005) pp. 2001–2007.Google Scholar
20.Komura, T., Nagano, A., Leung, H. and Shinagawa, Y., “Simulating pathological gait using the enhanced linear inverted pendulum model”, IEEE Trans. Biomed. Eng. 52 (9), 1502–1513 (2005).CrossRefGoogle ScholarPubMed
21.Kim, J. Y., Park, I. W. and Oh, J. H., “Walking control algorithm of biped humanoid robot on uneven and inclined floor,” J. Intell. Robot. Syst. 48 (4), 457–484 (2007).CrossRefGoogle Scholar
22.Kajita, S., Morisawa, M., Harada, K., Kaneko, K., Kanehiro, F., Fujiwara, K. and Hirukawa, H., “Biped Walking Pattern Generator Allowing Auxiliary ZMP Control,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China (2006) pp. 2993–2999.Google Scholar
23.Fernández, V., Balaguer, C., Blanco, D. and Salichs, M. A., “Active Human-Mobile Manipulator Cooperation Through Intention Recognition,” Proceedings of IEEE International Conference on Robotics and Automation (ICRA'01), Seoul, Korea (2001) pp. 2668–2673.Google Scholar
24.Monje, C. A., Pierro, P. and Balaguer, C., “Humanoid robot RH-1 for collaborative tasks: A control architecture for human-robot cooperation,” Appl. Bionics Biomech. 5 (4), 225–234 (2008).CrossRefGoogle Scholar
25.Nakamura, Y., Hanafusa, H. and Yoshikawa, T., “Task-priority based redundancy control of robot manipulators,” Int. J. Robot. Res. 6 (2), 3–15 (1987).CrossRefGoogle Scholar
26.Chiaverini, S. and Siciliano, B., “The unit quaternion: A useful tool for inverse kinematics of robot manipulators,” Syst. Anal. Model. Simul. 35, 45–60 (1999).Google Scholar
27.Perez, C., Pierro, P., Martínez, S., Pabón, L. A., Arbulú, M. and Balaguer, C., “RH-2: An Upgraded Full-Size Humanoid Platform,” 12th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines (CLAWAR'09), Istanbul, Turkey (2009).Google Scholar
28.Kumar, R. P., Yoon, J. W. and Kim, G. S., “Simplest Dynamic Walking Model with Toed Feet,” Proceedings of IEEE-RAS International Conference on Humanoid Robots, Daejeon, Korea (2008) pp. 245–250.Google Scholar
29.Kajita, S., Nagasaki, T., Yokoi, K., Kaneko, K. and Tanie, K., “Running Pattern Generation for a Humanoid Robot,” Proceedings of IEEE International Conference on Robotics and Automation, EEUU, Washington DC, (2002) pp. 2755–2761.Google Scholar
30.Arbulu, M., Stable Locomotion of Humanoid Robots Based on Mass Concentrated Model, Ph.D. Thesis., University Carlos III of Madrid, Madrid, Spain.Google Scholar
31.Kaynov, D., Open Motion Control Architecture for Humanoid Robots Ph.D. Thesis., University Carlos III of Madrid, Madrid, Spain.Google Scholar
32.Khalil, H. K., ed., Nonlinear Systems (Pearson Education, Upper Saddle River, NJ, 1999).Google Scholar
33.Isidori, J. A., ed., Nonlinear Control Systems (Springer-Verlag, London, 1995).CrossRefGoogle Scholar