Active power-assist exoskeletons are becoming more prospective than follow-up types, especially for elderly and handicapped motion auxiliary. The exoskeleton is required not only to withstand load but also to actively share the weight of a human body. Active power-assist lower limb is designed to meet this expectation. The definition of ''active powerassist'' was suggested in this article. A unique man-machine motion mapping was derived based on the configuration matching, wherein the exoskeleton obtains the wearer's motion data and parse out the corresponding intention. Manmachine coupling mechanisms were exquisitely configured, which rationalize the degrees of freedom of the manmachine system and facilitate force transmission for active assistant. The dynamic knees and hip joints with the integrated force servo unit were designed, which is the key to realize soft contact and cooperative movement. The prototype was developed, and three basic functions (human movement perception, force transmission, and movement cooperation) were preliminarily verified in a single leg swinging experiment. The effect of follow-up mode and active power-assist mode were quantitatively analyzed in marches-on-the-spot experiment. A 24.6% proportional reduction of the wearer foot force and smooth man-machine coordination in field experiments has demonstrated the feasibility of this structure design of active power-assist lower limb.

Exoskeleton robots demonstrate promise in their application in assisting or enhancing human physical capacity. Joint muscular torques (JMT) reflect human effort, which can be applied on an exoskeleton robot to realize an active power-assist function. The estimation of human JMT with a wearable exoskeleton is challenging. This paper proposed a novel human lower limb JMT estimation method based on the inverse dynamics of the human body. The method has two main parts: the inverse dynamic approach (IDA) and the sensing system. We solve the inverse dynamics of each human leg separately to shorten the serial chain and reduce computational complexity, and divide the JMT into the mass-induced one and the foot-contact-force (FCF)-induced one to avoid switching the dynamic equation due to different contact states of the feet. An exoskeleton embedded sensing system is designed to obtain the user’s motion data and FCF required by the IDA by mapping motion information from the exoskeleton to the human body. Compared with the popular electromyography (EMG) and wearable sensor based solutions, electrodes, sensors, and complex wiring on the human body are eliminated to improve wearing convenience. A comparison experiment shows that this method produces close output to a motion analysis system with different subjects in different motion.

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As macroscopic rough terrains are time varying and full of local topographic mutations, stable locomotions of legged robots moving through such terrains in a fixed gait form can be hardly obtained. This problem becomes more severe as the size and weight of the robot increase. An ideal pre-planned gait changing method can also be hardly designed due to the same limitations. Aiming to solve the problem, a new kind of free gait controller applied to a large-scale hexapod robot with heavy load is developed. The controller consists of two parts, a free gait planner and a gait regulator. Based on the observed macro terrain changes, the free gait planner adopts the macro terrain recognition method and the status searching method for selecting the best leg support status automatically. The gait regulator is adopted for the correction of the selected status to cope with local topographic mutations. Detailed simulation experiments are presented to demonstrate that, with the designed controller, the adopted hexapod robot can change moving gaits automatically in terms of the terrain conditions and obtain stable locomotions through rough terrains.