The large number of patients with ankle injuries and the high incidence make ankle rehabilitation an urgent health problem. However, there is a certain degree of difference between the motion of most ankle rehabilitation robots and the actual axis of the human ankle. To achieve more precise ankle joint rehabilitation training, this paper proposes a novel 3-PUU/R parallel ankle rehabilitation mechanism that integrates with the human ankle joint axis. Moreover, it provides comprehensive ankle joint motion necessary for effective rehabilitation. The mechanism has four degrees of freedom (DOFs), enabling plantarflexion/dorsiflexion, eversion/inversion, internal rotation/external rotation, and dorsal extension of the ankle joint. First, based on the DOFs of the human ankle joint and the variation pattern of the joint axes, a 3-PUU/R parallel ankle joint rehabilitation mechanism is designed. Based on the screw theory, the inverse kinematics inverse, complete Jacobian matrix, singular characteristics, and workspace analysis of the mechanism are conducted. Subsequently, the motion performance of the mechanism is analyzed based on the motion/force transmission indices and the constraint indices. Then, the performance of the mechanism is optimized according to human physiological characteristics, with the motion/force transmission ratio and workspace range as optimization objectives. Finally, a physical prototype of the proposed robot was developed, and experimental tests were performed to evaluate the above performance of the proposed robot. This study provides a good prospect for improving the comfort and safety of ankle joint rehabilitation from the perspective of human-machine axis matching.

In order to make a fast and accurate response to gas leakage event, e.g. gas leakage in hydrogen storage station, it is very important to identify and locate the leakage source accurately and quickly. Due to the flexibility and the adaptability of robots to harsh environments, leakage source tracing based on mobile robots has attracted more and more attention. However, the existing ground robots are limited by the ground environment and thus it is difficult to trace and locate the leakage in the complex environment with ground robots. Although unmanned aerial vehicle (UAV) can overcome the limitation of ground obstacles, there are still some problems in the accuracy and reliability of gas sampling due to the interference of flow field caused by UAV rotors to the surrounding gases. Based on computational fluid dynamic simulation, a simulation model of UAV with four rotors was established. Combined with test experiments, the influence of flow field around UAV on gas sampling under different UAV speeds, rotors assembly structures, leakage, and sampling conditions was analyzed and investigated. The optimized UAV assembly structure and gas sensor installation position were determined and verified by the simulations and experiments. The results showed that the sensor was less affected by the rotor airflow when the UAV rotor was reversely assembled and the gases were sampled above the UAV. This research can provide a guidance for gas sampling for emission source tracing with UAV for process safety management of energy gas storage.