Adaptive control of leg position for hexapod robot based on somatosensory feedback and organic computing principles

Improving robot walking over compliant surfaces is considered an important issue. However, walking on an uneven surface requires controlling the robot‘s leg position to span a varying distance between the robot’s body and the ground. This paper will shed light on the applied decentralized controller approach that enables the robot‘s leg to adapt its position to be commensurate with the type of walking surface in order to improve walking on compliant surfaces. When the substrate compliance is high (sandy ground), the leg has to correct its position close to the point of contact with the ground. When the substrate compliance is low (gravel ground), the correction of the leg position is low. The novelty of our approach is the evaluation of the local current consumption and the angular position of each leg’s joint as somatosensory feedback. Our approach is based on an organic computing architecture and was tested on a low-cost version of the OSCAR walking robot.