Slippery and sandy ground detection for hexapod robots based on organic computing principles and somatosensory feedback

Insect-like walking of six-legged robots on unstructured and rough terrain is considered a challenging task. Furthermore, the properties of the walking ground are considered an important issue and a challenge to insure stable adaptive walking. This paper will shed light on the applied decentralized controller approach for detecting slippery and sandy ground and also presents the proposed strategies to overcome these challenges. The novelty of our approach is the evaluation of the local current consumption and angular position of each leg's joint as somatosensory feedback. Backward walking is proposed as a reflex reaction once a slippery ground is detected and an adaptive walking as soon as the robot detects sandy ground. Our approach is based on an organic computing architecture and was tested on a low-cost version of the OSCAR walking robot.