Integration of multi sensors for adaptive walking of a quadruped robot

IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems

Volumn 2003-January, Issue , 2003, Pages 21-26

  Fukuoka, Y ^a   Mimura, T ^a   Yasuda, N ^a   Kimura, H ^a  

^a UNIVERSITY OF ELECTRO COMMUNICATIONS   (Japan)

Author keywords

Biological system modeling; Biosensors; Brain modeling; Hip; Leg; Legged locomotion; Neurofeedback; Neurons; Robot sensing systems; Sensor systems

Indexed keywords

BIOFEEDBACK; BIOSENSORS; BRAIN MODELS; HOT ISOSTATIC PRESSING; INTEGRATION; INTELLIGENT SYSTEMS; MOTION PICTURE EXPERTS GROUP STANDARDS; MULTIPURPOSE ROBOTS; NEURONS; ROBOTS;

BIOLOGICAL SYSTEM MODELING; LEG; LEGGED LOCOMOTION; NEUROFEEDBACK; ROBOT SENSING SYSTEM; SENSOR SYSTEMS;

BIOLOGICAL SYSTEMS;

EID: 33644900662     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MFI-2003.2003.1232572     Document Type: Conference Paper

References (17)

1. Grillner, S. 1981. Control of locomotion in bipeds, tetrapods and fish. Handbook of Physiology II. American Physiol. Society, Bethesda, MD. 1179-1236.
2. Cohen, A. H., and Boothe, D. L. 1999. Sensorimotor interactions during locomotion: principles derived from biological systems. Autonomous Robots. 7(3):239-245.
3. Taga, G., Yamaguchi, Y., and Shimizu, H. 1991. Self-organized control of bipedal locomotion by neural oscillators. Biolog. Cybern. 65:147-159.
4. Taga, G. 1995. A model of the neuro-musculoskeletal system for human locomotion II. - real-time adaptability under various constraints. Biolog. Cybern. 73:113-121.
5. Ijspeert, A.J. 2001. A connectionist central pattern generator for the aquatic and terrestrial gaits of a simulated salamander. Biolog. Cybern. 84(5):331-348.
6. Kimura, H., Akiyama, S., and Sakurama, K. 1999. Realization of dynamic walking and running of the quadruped using neural oscillator. Autonomous Robots. 7(3):247-258.
7. Ilg, W., Albiez, J., Jedele, H., Berns, K., and Dillmann, R. 1999. Adaptive periodic movement control for the four legged walking machine BISAM. Proc. of ICRA1999, pp. 2354-2359.
8. Tsujita, K., Tsuchiya, K., et al. 2001. Adaptive Gait Pattern Control of a Quadruped Locomotion Robot, Proc. of IROS2001, pp. 305-310.
9. Kimura, H., Fukuoka, Y., et al. 2001. Adaptive dynamic walking of a quadruped robot using neural system model. Advanced Robotics. 15(8):859-876.
10. Lewis, M. A., Etienne-Cummings, Hartmann, M. J., Xu, Z. R., and Cohen, A. H. 2003. An in silico central pattern generator: silicon oscillator, coupling, entrainment, and physical computation. Biolog. Cybern. 88:137-151.
11. Fukuoka, Y., Kimura, H., Cohen, A.H. 2003. Adaptive Dynamic Walking of a Quadruped Robot on Irregular Terrain based on Biological Concepts. Int. J. Robotics Research. 22(2):(in Press)
12. Matsuoka, K. 1987. Mechanisms of frequency and pattern control in the neural rhythm generators. Biolog. Cybern. 56:345-353.
13. Full, R. J., and Koditschek, D. E. 1999. Templates and anchors: neuromechanical hypotheses of legged locomotion on land. J. Exp. Biol. 202:3325-3332.
14. Full, R. J. 2000. Biological inspiration: lessons from many-legged locomotors. Robotics Research 9, J.M.Hollerbach and D.E.Koditschek Eds, Springer London. 337-341.
15. Saranli, U., Buehler, M., and Koditschek, D. E. 2001. RHex: a simple and highly mobile hexapod robot. Int. J. Robotics Research. 20(7):616-631.
16. Cham, J. G., Bailey, S. A., Clark J. E., Full, R. J., Cutkosky, M. R., Fast and Robust: Hexapedal Robots via Shape Deposition Manufacturing, Int. J. Robotics Research 21(10-11):869-882, 2002.
17. Lewis, M. A. 2002. Detecting Surface Features During Locomotion Using Optic Flow. Proc. of ICRA2002, pp. 305-310.