Developing robust and reliable control code for autonomous mobile robots is difficult, because the interaction between a physical robot and the environment is highly complex, subject to noise and variation, and therefore partly unpredictable. This means that to date it is not possible to predict robot behaviour based on theoretical models. Instead, current methods to develop robot control code still require a substantial trial-and-error component to the software design process. This paper proposes a method of dealing with these issues by (a) establishing task-achieving sensor-motor couplings through robot training, and (b) representing these couplings through transparent mathematical functions that can be used to form hypotheses and theoretical analyses of robot behaviour. We demonstrate the viability of this approach by teaching a mobile robot to track a moving football and subsequently modelling this task using the NARMAX system identification technique.
|Number of pages||9|
|Journal||Robotics and Autonomous Systems|
|Early online date||04 Jun 2007|
|Publication status||Published - 30 Sept 2007|
- Autonomous mobile robots
- System identification