An adaptive gait planner for a lower-limb exoskeleton ascending staircases of unknown geometry

The staircase ascent motion is a physical activity which is very common in everyday life, but it is very challenging for people who suffer for Spinal Cord Injury (SCI). Active exoskeletons can help patients to regain a certain degree of mobility, but their design require facing some difficult problems: smart exoskeletons need to perceive the environment and, in turn, adapt the gait, so as to guarantee a smooth and safe motion. In such a context, this work proposes a solution for a staircase ascending problem. It exploits low cost ranging sensors for the environment reconstruction and a real-time trajectory planner for the generation of an adaptive gait which accounts for the steps geometry. The strength of the proposed technique is represented by the continuous update method -- adopted for both the environment reconstruction and the path planning -- which allows for a safe ascent. The proposed method was tested through simulations and real experiments.