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Survey of Intelligent Control Techniques for Humanoid Robots

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Abstract

This paper focusses on the application of intelligent control techniques (neural networks, fuzzy logic and genetic algorithms) and their hybrid forms (neuro-fuzzy networks, neuro-genetic and fuzzy-genetic algorithms) in the area of humanoid robotic systems. It represents an attempt to cover the basic principles and concepts of intelligent control in humanoid robotics, with an outline of a number of recent algorithms used in advanced control of humanoid robots. Overall, this survey covers a broad selection of examples that will serve to demonstrate the advantages and disadvantages of the application of intelligent control techniques.

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References

  • Arakawa, T. and Fukuda, T.: 1997, Natural motion generation of biped locomotion robot using hierarchical trajectory generation method consisting of GA, EP layers, in: Proc. of the IEEE Internat. Conf. on Robotics and Automation, Albuquerque, USA, April, pp. 211-216.

  • Arkin, R. C.: 1999, Behaviour-Based Robotics, MIT Press, Cambridge, MA, USA.

    Google Scholar 

  • Billard, A. and Mataric, M.: 2000, Learning human arm movements by imitation: Evaluation of a biologically-inspired connectionist algorithms, in: Proc. of the IEEE Internat. Conf. on Humanoid Robots HUMANOIDS 2000, Cambridge, MA, USA, September.

  • Brooks, R. A.: 1997, From earwigs to humans, Robotics Autonom. Systems 20(2-4), 291-304.

    Google Scholar 

  • Capi, G., Nasu, Y., Barolli, L., Yamano, M., Mitobe, K., and Takeda, K.: 2001, A neural network implementation of biped robot optimal gait during walking generated by genetic algorithm, in: Proc. of the 9th Mediterranean Conf. on Control and Automation, Dubrovnik, Croatia, June.

  • Cheng, M.-Y. and Lin, C.-S.: 1997, Genetic algorithm for control design of biped locomotion, J. Robotic Systems 14(5), 365-373.

    Google Scholar 

  • Doerschuk, P. I., Simon, W. E., Nguyen, V., and Li, A.: 1998, A modular approach to intelligent control of a simulated jointed leg, IEEE Robotics Automat. Mag. 5(2), 12-21.

    Google Scholar 

  • Doya, K., Kimura, H., and Kawato, M.: 2001, Neural mechanisms of learning and control, IEEE Control Systems Mag. 21(4), 42-54.

    Google Scholar 

  • Endo, K., Yamasaki, F., Maeno, T., and Kitano, H.: 2002, A method for co-evolving morphology and walking pattern of biped humanoid robot, in: Proc. of the 2002 IEEE Internat. Conf. on Robotics and Automation, Washington, DC, USA, May, pp. 2159-2164.

  • Fukuda, T., Komata, Y., and Arakawa, T.: 1997, Stabilization control of biped locomotion robot based learning with GAs having self-adaptive mutation and recurrent neural network, in: Proc. of the IEEE Internat. Conf. on Robotics and Automation, Albuquerque, USA, April, pp. 217-222.

  • Garcia, L.-M., Oliveira, A. A. F., Grupen, R. A., Wheeler, D. S., and Fagg, A. H.: 2000, Tracing patterns and attention: Humanoid robot cognition, IEEE Intelligent Systems (July/August), 70-77.

  • Giszter, S. F., Moxon, K. A., Rybak, I. A., and Chaplin, J. K.: 2000, Neurobiological and neurorobotic approaches to a control architecture for a humanoid motor system, IEEE Intelligent Systems (July/August), 64-69.

  • Goldberg, D. E.: 1989, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, MA, USA.

    Google Scholar 

  • Goswami, A.: 1999, Postural stability of biped robots and the foot-rotation indicator point, Internat. J. Robotics Res. 18(6), 523-533.

    Google Scholar 

  • Guihard, M. and Gorce, P.: 2001, Dynamic control of a biomechanical inspired biped: BIPMAN, in: Proc. of the 4th Internat. Conf. on Climbing and Walking Robots, Karlsruhe, Germany, September.

  • Haupt, R. and Haupt, S. E.: 1998, Practical Genetic Algorithms, Wiley, New York.

    Google Scholar 

  • Haykin, S.: 1994, Neural Networks - A Comprehensive Foundation, Vols. 1, 2, Mackmillan, Englewood Cliffs, NJ, USA.

  • Hirai, K.: 1997, Current and future perspective of Honda humanoid robot, in: Proc. of the IEEE/RSJ Internat. Conf. on Intelligent Robotics and Systems IROS, pp. 500-508.

  • Hirai, K., Hirose, M., Haikawa, Y., and Takenaka, T.: 1998, The development of Honda humanoid robot, in: Proc. of the IEEE Internat. Conf. on Robotics and Automation, Leuven, Belgium, May, pp. 1321-1326.

  • Hu, J., Pratt, J., and Pratt, G.: 1999, Stable adaptive control of a bipedal walking robot with CMAC neural networks, in: Proc. of the 1999 IEEE Internat. Conf. on Robotics and Automation, Detroit, USA, May, pp. 1950-1956.

  • Huang, Q., Nakamura, Y., and Inamura, T.: 2001, Humanoids walk with feedforward dynamic pattern and feednack sensory reflection, in: Proc. of the 2001 IEEE Internat. Conf. on Robotics and Automation, Seoul, Korea, May, pp. 4220-4225.

  • Ivanescu, M., Popescu, A. M., and Popescu, D.: 2001, Moving target interception for a walking robot by fuzzy observer and fuzzy controller, in: Proc. of the 4th Internat. Conf. on Climbing and Walking Robots, Karlsruhe, Germany, September.

  • Juang, J.-G.: 2000, Fuzzy neural network approaches for robotic gait synthesis, IEEE Trans. Systems Man Cybernet., Part B: Cybernetics 30(4), 594-601.

    Google Scholar 

  • Juang, J.-G. and Lin, C.-S.: 1996, Gait synthesis of a biped robot using backpropagation through time algorithm, in: Proc. of the IEEE Internat. Joint Conf. on Neural Networks, Washington, DC, USA, pp. 1710-1715.

  • Kawato, M.: 1999, Internal models for motor control and trajectory planning, Current Opinion Neurobiology 12, 718-727.

    Google Scholar 

  • Kawato, M., Uno, Y., Isobe, R., and Suzuki, R.: 1987, Hierarchical neural network model for voluntary movement with application to robotics, IEEE Control Systems Mag. 57, 169-185.

    Google Scholar 

  • Kiriazov, P.: 2001, Learning robots to move: Biological control concepts, in: Proc. of the 4th Internat. Conf. on Climbing and Walking Robots, Karlsruhe, Germany, September.

  • Kitamura, S., Kurematsu, Y., and Nakai, Y.: 1988, Application of the neural network for the trajectory planning of a biped locomotion robot, Neural Networks 1, 344-356.

    Google Scholar 

  • Klute, G. K., Czerniecki, J. M., and Hannaford, B.: 1999, Pneumatic actuators with biomechanical intelligence, in: Proc. of the IEEE/ASME Internat. Conf. on Advanced Intelligent Mechatronics, Atlanta, USA, September.

  • Kun, A. L. and Miller, III, W. T.: 1999, Control of variable - speed gaits for a biped robot, IEEE Robotics Automat. Mag. 6(3), 19-29.

    Google Scholar 

  • Kurematsu, Y., Katayama, O., Iwata, M., and Kitamura, S.: 1991, Autonomous trajectory generation of a biped locomotive robot, in: Proc. of the IEEE Internat. Joint Conf. on Neural Networks, pp. 1983-1988.

  • Marchese, S., Muscato, G., and Virk, G. S.: 2001, Dynamically stable trajectory synthesis for a biped robot during the single-support phase, in: Proc. of the 2001 IEEE/ASME Internat. Conf. on Advanced Intelligent Mechatronics, Como, Italy, May, pp. 953-958.

  • Mataric, M. et al.: 1998, Behaviour-based primitives for articulated control, in: Proc. of the 5th Internat. Conf. on Soc. for Adaptive Behaviours, MIT Press, Cambridge,MA, USA, pp. 165-170.

    Google Scholar 

  • Miller, III, W. T.: 1994, Real-time neural network control of a biped walking robot, IEEE Control Systems Mag. (February), 41-48.

  • Miller, III, W. T., Glanz, F. H., and Kraft, L. G.: 1987, Application of a general learning algorithm to the control of robotic manipulators, Internat. J. Robotics Reserach 6(2).

  • Nagasaka, K., Konno, A., Inaba, M., and Inoue, H.: 1997, Acquisition of visually guided swing motion based on genetic algorithms and neural networks in two-armed bipedal robot, in: Proc. of the IEEE Internat. Conf. on Robotics and Automation, Albuquerque, USA, April, pp. 2944-2949.

  • Pettersson, J., Sandholt, H., and Wahde, H.: 2001, A flexible evolutionary method for the generation and implementation of behaviours for humanoid robots, in: Proc. of the IEEE-RAS Internat. Conf. on Humanoid Robots HUMANOIDS 2001, Tokyo, Japan, November.

  • Pfeiffer, F., Loffler, K., and Gienger, M.: 2002, The concept of jogging JOHNNIE, in: Proc. of the 2002 IEEE Conf. on Robotics and Automation, Washington, DC, USA, May, pp. 3129-3135.

  • Raibert, M.: 1986, Legged Robots that Balance, MIT Press, Cambridge, MA, USA.

    Google Scholar 

  • Reil, T. and Husbands, P.: 2002, Evolution of central pattern generators for bipedal walking in a real-time physics environment, IEEE Trans. Evolutionary Comput. 6(2), 159-168.

    Google Scholar 

  • Rumelhart, D. E. and McClelland, J. L.: 1986, Parallel Distributed Processing (PDP): Exploration in the Microstructure of Cognition, Vols. 1, 2, MIT Press, Cambridge, MA, USA.

    Google Scholar 

  • Salatian, W., Yi, K. Y., and Zheng, Y. F.: 1997, Reinforcement learning for a biped robot to climb sloping surfaces, J. Robotic Systems 14(4), 283-296.

    Google Scholar 

  • Salatian, W. and Zheng, Y. F.: 1992a, Gait synthesis for a biped robot climbing sloping surfaces using neural networks I. Static learning, in: Proc. of the IEEE Internat. Conf. on Robotics and Automation, Nice, France, May, pp. 2601-2606.

  • Salatian, W. and Zheng, Y. F.: 1992b, Gait synthesis for a biped robot climbing sloping surfaces using neural networks II. Dynamic learning, in: Proc. of the IEEE Internat. Conf. on Robotics and Automation, Nice, France, May, pp. 2607-2611.

  • Sardain, P. and Bessonnet, G.: 2001, Gait analysis of a human walker wearing robot feet as shoes, in: Proc. of the 2001 IEEE Internat. Conf. on Robotics and Automation, Seoul, Korea, May, pp. 2285-2292.

  • Sardain, P., Rostami, M., and Bessonnet, G.: 1998, An anthropomorphic biped robot: Dynamic concepts and technological details, IEEE Trans. Systems Man Cybernet., Part A: Systems and Humans 28(6), 823-838.

    Google Scholar 

  • Schulz, S. and Bretthauer, G.: 2001, A fluidic humanoid robothand, in: Proc. of the IEEE-RAS Internat. Conf. on Humanoid Robots HUMANOIDS 2001, Tokyo, Japan, November.

  • Terano, T., Asai, K., and Sugeno, M.: 1992, Fuzzy Systems Theory and Its Applications, Academic Press, Boston, USA.

    Google Scholar 

  • Vijayakumar, S. and Schaal, S.: 2000, Real time learning in humanoids: A challenge for scalability algorithms, in: Proc. of the IEEE Internat. Conf. on Humanoid Robots HUMANOIDS 2000, Cambridge, MA, USA, September.

  • Vukobratović, M., Borovac, B., and Surdilovic, D.: 2002, Zero-moment point - proper interpretation and the application in gait control, Intelligent J. Engrg. Automat. Problems 3, 3-14.

    Google Scholar 

  • Vukobratović, M. and Timčenko, O.: 1995, Stability analysis of certain class of bipedal walking robots with hybridization of classical and fuzzy control, in: Proc. of the 1st ECPD Internat. Conf. on Advanced Robotics and Intelligent Automation, Athens, Greece, pp. 290-295.

  • Wang, H., Lee, T. T., and Gruver, W. A.: 1992, A neuromorphic controller for a three link biped robot, IEEE Trans. Systems Man Cybernet. 22(1), 164-169.

    Google Scholar 

  • www.androidworld.com

  • www.symbio.jst.go.jp

  • www.world.honda.com/robot

  • Yamaguchi, J. J. et al.: 1998, Development of a bipedal humanoid robot - control method of whole body cooperative dynamic biped walking, in: Proc. of the IEEE Internat. Conf. on Robotics and Automation, Leuven, Belgium, May, pp. 3801-3806.

  • Yamazaki, F., Matsui, T., Miyashita, T., and Kitano, H.: 2000, PINO - the humanoid that walks, in: Proc. of the 1st IEEE-RAS Internat. Conf. on Humanoid Robotis.

  • Yang, A. and Low, K. H.: 2002, Fuzzy position/force control of a robot leg with a flexible gear system, in: Proc. of the 2002 IEEE Conf. on Robotics and Automation, Washington, DC, USA, May, pp. 2159-2164.

  • Yoshikawa, Y., Asada, M., and Hosoda, K.: 2001, Development approach to spatial perception for imitation learning incremental demonstrator's view, in: Proc. of the IEEE-RAS Internat. Conf. on Humanoid Robots HUMANOIDS 2001, Tokyo, Japan, November.

  • Zheng, Y. P. and Shen, J.: 1990, Gait synthesis for the SD-2 biped robots to climb sloping surface, IEEE Trans. Robotics Automat. 6(1), 86-96.

    Google Scholar 

  • Zhou, D. and Low, K. H.: 2001, Combined use of ground learning model and active compliance to the motion control of walking robotic legs, in: Proc. of the 2001 IEEE Internat. Conf. on Robotics and Automation, Seoul, Korea, May, pp. 3159-3164.

  • Zhou, C. and Meng, Q.: 2000, Reinforcement learning with fuzzy evaluative feedback for a biped robot, in: Proc. of the IEEE Internat. Conf. on Robotics and Automation, San Francisko, CA, USA, pp. 3829-3834.

  • Zimmermann, H.-J.: 1990, Fuzzy Sets Theory and Its Applications, Kluwer Academic Publishers, Dordrecht, The Netherlands.

    Google Scholar 

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  1. Robotics Laboratory, Mihailo Pupin Institute, Volgina 15, 11000, Belgrade, Yugoslavia

    Duško Katić & Miomir Vukobratović

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  1. Duško Katić
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  2. Miomir Vukobratović
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Katić, D., Vukobratović, M. Survey of Intelligent Control Techniques for Humanoid Robots. Journal of Intelligent and Robotic Systems 37, 117–141 (2003). https://doi.org/10.1023/A:1024172417914

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