An adaptive actor-critic algorithm with multi-step simulated experiences for controlling nonholonomic mobile robots
| Main Author: | Syam, Rafiuddin |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
Springer, Germany, Vol. 11 No. 1 January 2007
, 2012
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| Subjects: | |
| Online Access: |
http://repository.unhas.ac.id/handle/123456789/2640 |
Daftar Isi:
- In this paper, we propose a new algorithm of an adaptive actor-critic method with multi-step simulated experiences, as a kind of temporal difference (TD) method. In our approach, the TD-error is composed of two valuefunctions and m utility functions, where m denotes the number ofmulti-steps inwhich the experience should be simulated. The value-function is constructed from the critic formulated by a radial basis function neural network (RBFNN), which has a simulated experience as an input, generated from a predictive model based on a kinematic model. Thus, since our approach assumes that the model is available to simulate the m-step experiences and to design a controller, such a kinematic model is also applied to construct the actor and the resultant model based actor (MBA) is also regarded as a network, i.e., it is just viewed as a resolved velocity control network. We implement this approach to control nonholonomic mobile robot, especially in a trajectory tracking control problem for the position coordinates and azimuth. Some simulations show the effectiveness of the proposed method for controlling a mobile robot with two-independent driving wheels.