Virtual Sensor Verification Using Neural Network Theory of the Quadruped Robot

The sensor data measured by the legged robot are used to recognize the physical environment or information that controls the robot`s posture. Therefore, a robot`s ambulation can be advanced with the use of such sensing information. For the precise control of a robot, highly accurate sensor data are required, but most sensors are expensive and are exposed to excessive load operation in the field. The seriousness of these problems will be seen if the prototype`s practicality and mass productivity, which are closely related to the unit cost of production and maintenance, will be considered. In this paper, the use of a virtual sensor technology was suggested to address the aforementioned problems, and various ways of applying the theory to a walking robot obtained through training with an actual sensor, and of various hardware information, were presented. Finally, the possibility of the replacement of the ground reaction force sensor of legged robot was verified.

[1]  Manuela M. Veloso,et al.  CMPack: a complete software system for autonomous legged soccer robots , 2001, AGENTS '01.

[2]  Yehoshua Y. Zeevi,et al.  Neural networks: theory and applications , 1992 .

[3]  Nadine N. Tschichold-Gürman,et al.  The development of a robot terrain interaction system for walking machines , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[4]  P. Gonzalez de Santos,et al.  Neural virtual sensors for terrain adaptation of walking machines , 2005 .

[5]  Steven Dubowsky,et al.  Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers , 2004, IEEE Transactions on Robotics.

[6]  Xiaoming Hu,et al.  Nonlinear pitch and roll estimation for walking robots , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).