Legged locomotion is of major interest both for robotics – developing versatile robots that can maneuver in general terrain, and for rehabilitation – developing systems that restore mobility to the disabled. Dynamic legged locomotion is a promising alternative to quasi-static locomotion, since it produces faster, and more efficient human-like gaits. However the development of dynamically stable walking robots, which can adapt their gait on-line to the terrain, is still a challenge.
Research on animal locomotion suggests that biological gaits are produced by networks of coupled neural oscillators that generate the required rhythmic patterns of muscles activation. These networks, known as Central Pattern Generators (CPGs) can maintain the required rhythmic activity even without any sensory feedback. Nevertheless, sensory feedback can enhance stability and robustness to perturbations – and the issue of what feedback should be used and how it should be integrated with the network of coupled oscillators is a major research topic. We have developed a unique approach which integrates a once-per-step feedback and demonstrated that it improves robustness and adaptability to slope variations for the simple compass-gait biped model.
The research on biped locomotion is expected to improve the development of:
- Biped and humanoid robots
- Exoskeletons for walking assistance, like ReWalk by ARGO – a wearable exoskeleton that restores upright mobility, and
- Neuro-rehabilitation of locomotion, like the NES L300 by BioNess, which activates the nerves that control the muscles to lift the foot.