Motion Control of the Brachiation Type of Mobile Robot Using Cerebellar Neural Model
Fuminori Saito*, Toshio Fukuda** and Fumihito Arai**
*Graduate School at Nagoya University
** Department of Mechano-Informatics and Systems at Nagoya University, 1 Furo-cho, Chikusa-ku, Nagoya, Aichi 46401, Japan
In our previous study, we confirmed the effectiveness of the heuristic method to control a brachiation robot (BMR) that we have proposed. In addition, we proposed a method using the spline interpolation to obtain suitable driving inputs for unexperienced targets derived from already experienced targets. In this paper, in order to obtain driving inputs in the case of multiple changes of control situations, we use a CMAC neural model to interpolate driving inputs obtained from experiences. Furthermore, we use trajectory feedback control and arm-direction feedback control to achieve precise laddercatching.