Successful results from training an adaptive controller to use optical information to balance an inverted pendulum are presented in comparison to the training requirements using traditional controller inputs. Results from research into the psychology of the sense of balance in humans are presented as the motivation for the investigation of this new type of controller. The simulated model of the inverted pendulum and the virtual reality environments used to provide the optical input are described The successful introduction of optical information is found to require the preservation of at least two of the traditional input types and entail increased training time for the adaptive controller and reduced performance (measured as the time the pendulum remains upright).
|Title of host publication
|2004 IEEE International Conference on Systems, Man and Cybernetics
|Place of Publication
|Institute of Electrical and Electronics Engineers Inc.
|Published - 2004
- artificial neural network, reinforcement learning, real time, controller, first order optic flow algorithms, affine parameters