This work investigates how arm swing movements measured by Inertial Motion Unit (IMU) sensors can be used to identify and maintain the walking state in a self-balanced lower-limb exoskeleton for medical use. When an exoskeleton is in a dynamical state during gait, short patterns in IMU signals (e.g. a braking movement) can be hard to extract. Therefore, by relying on a threshold-based classifier constructed upon descriptive features of actively maintained arm swing movements, it is possible to build a gait termination detection method in which the transition between the walking and standstill states occurs whenever arm movements cease, and the corresponding patterns in the IMU signals disappear. Analysis of arm IMU signals were used to identify three amplitude and coordination-based features for the classification architecture. An online implementation of this novel detection interface for maintaining the walking state was validated with 11 unimpaired participants using the Atalante exoskeleton, leading to high accuracy with less than 2% of false negatives when the arms were swinging at a high amplitude, and less than 15% when they were swinging at a medium amplitude.

The new robot called BeeRotor we have developed is a tandem rotorcraft that mimicks optic flow-based behaviors previously observed in flies and bees. This tethered miniature robot (80g), which is autonomous in terms of its computational power requirements, is equipped with a 13.5-g quasi-panoramic visual system consisting of 4 individual visual motion sensors responding to the optic flow generated by photographs of natural scenes, thanks to the bio-inspired “time of travel” scheme. Based on recent findings on insects' sensing abilities and control strategies, the BeeRotor robot was designed to use optic flow to perform complex tasks such as ground and ceiling following while also automatically driving its forward speed on the basis of the ventral or dorsal optic flow. In addition, the BeeRotor robot can perform tricky manoeuvers such as automatic ceiling docking by simply regulating its dorsal or ventral optic flow in high-roofed tunnel depicting natural scenes. Although it was built as a proof of concept, the BeeRotor robot is one step further towards achieving a fully-autonomous micro-helicopter which is capable of navigating mainly on the basis of the optic flow.