The design and the control of humanoid robots are one of the most challenging topics in the field of robotics and were treated by a large number of research works over the past decades (Bekey, 2005) (Vukobratovic, 1990). The potential applications of this field of research are essential in the middle and long term. First, it can lead to a better understanding of the human locomotion mechanisms. Second, humanoid robots are intended to replace humans to work in hostile environments or to help them in their daily tasks. Today, several prototypes, among which the most remarkable are undoubtedly the robots Asimo (Sakagami , 2002) and HRP-2 (Kaneko, 2004), have proved the feasibility of humanoid robots. But, despite efforts of a lot of researchers around the world, the control of the humanoid robots stays a big challenge. Of course, these biped robots are able to walk but their basic locomotion tasks are still far from equalizing the human’s dynamic locomotion process. This is due to the fact that the control of biped robot is very hard because of the five following points: • Biped robots are high-dimensional non-linear systems, • Contacts between feet and ground are unilateral, • During walking, biped robots are not statically stable, • Efficient biped locomotion processes require optimisation and/or learning phases, • Autonomous robots need to take into account of exteroceptive information. Because of the difficulty to control the locomotion process, the potential applications of these robots stay still limited. Consequently, it is essential to develop more autonomous biped robots with robust control strategies in order to allow them, on the one hand to adapt their gait to the real environment and, on the other hand, to counteract external perturbations. In the autonomous biped robots’ control framework, our aim is to develop an intelligent control strategy for the under-actuated biped robot RABBIT (figure 1) (RABBIT-web) (Chevallereau, 2003). This robot constitutes the central point of a project, within the framework of CNRS ROBEA program (Robea-web), concerning the control of walking and running biped robots. The robot RABBIT is composed of two legs and a trunk and has no foot. Although the mechanical design of RABBIT is uncomplicated compared to other biped
[1]
George A. Bekey,et al.
AUTONOMOUS ROBOTS, From Biological Inspiration to Implementation and Control, by G.A. Bekey, MIT Press, 2005, xv + 577 pp., index, ISBN 0-262-02578-7, 25 pages of references (Hb. £35.95)
,
2005,
Robotica.
[2]
Christine Chevallereau,et al.
RABBIT: a testbed for advanced control theory
,
2003
.
[3]
M. Vukobratovic,et al.
Biped Locomotion
,
1990
.
[4]
James S. Albus,et al.
New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)1
,
1975
.
[5]
CHRISTOPHE SABOURIN,et al.
Start, Stop and Transition of Velocities of an under-Actuated Bipedal Robot without Reference Trajectories
,
2004,
Int. J. Humanoid Robotics.
[6]
Judy A. Franklin,et al.
Biped dynamic walking using reinforcement learning
,
1997,
Robotics Auton. Syst..
[7]
Gabriel Buche,et al.
Control Strategy for the Robust Dynamic Walk of a Biped Robot
,
2006,
Int. J. Robotics Res..
[8]
James S. Albus,et al.
Data Storage in the Cerebellar Model Articulation Controller (CMAC)
,
1975
.
[9]
Fumio Kanehiro,et al.
Humanoid robot HRP-2
,
2008,
IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.
[10]
Kikuo Fujimura,et al.
The intelligent ASIMO: system overview and integration
,
2002,
IEEE/RSJ International Conference on Intelligent Robots and Systems.
[11]
Christophe Sabourin,et al.
Robustness of the dynamic walk of a biped robot subjected to disturbing external forces by using CMAC neural networks
,
2005,
Robotics Auton. Syst..
[12]
W. T. Miller,et al.
CMAC: an associative neural network alternative to backpropagation
,
1990,
Proc. IEEE.
[13]
T. Michael Knasel,et al.
Robotics and autonomous systems
,
1988,
Robotics Auton. Syst..