Development of An Assist Upper Limb Exoskeleton For Manual Handling Task In this paper we describe the construction of a wearable upper arm exoskeleton to provide support for industrial workers who engaged in repetitive handling tasks and patients who full or partial loss of function in their upper limb due to accident injuries, spinal cord and strokes. We use flexible rope driven by a motor to realize the shoulder and elbow joints linkage, use ball screw to realize the selflocking in any position to providing assist for users. This novel design not only saves energy but also make the whole system portable. The total weight of the prototype is only 2 kg. The exoskeleton is connected upper limb with 3 bandages, and users take about 30 seconds to put it on and 20 seconds to put the exoskeleton off without any help. The PD adaptive control method is applied to the proposed exoskeleton to track expected trajectories. Five healthy people participated in data acquisition. Upper limb muscle integrated electromyography (IEMG) of the deltoid muscle(DM), the biceps femoris muscle (BFW), the femoral muscle (FM), the femoral wrist flexor (FWF) were compared in continuous handling for four different loads (0, 1.5, 3, 4.5kg). The average assistance efficiency were 39.1%, 41.5%, 36.5% and 40.6% for the DM, BFM, FM and FWF respectively. The experimental data show that the upper limb exoskeleton can provide assist for workers and protect their upper limbs injuries in longterm handling task.

Development of An Adaptive Iterative Learning Controller With Sensorless Force Estimator for The Hiptype Exoskeleton Nowadays industrial loads lifting still heavily relies on manual operation. Longterm lifting job can hugely increase low back strains and even cause lumbar diseases. With the rapid development of exoskeleton systems, it is essential to develop a hiptype exoskeleton for the porters. This paper proposes a modified adaptive iterative learningbased control algorithm with a sensorless force estimator. The advantage of this algorithm is that the exoskeleton joint can move precisely along the desired trajectory as well as generate an external assistance torque based on the force estimator while the wearer lifting the load. A hiptype exoskeleton device has been developed to evaluate the effectiveness of this algorithm. We carried out experiment works of bending and lifting heavy loads. Experimental results show that when choosing the IEMG of LES as the evaluation criteria, our exoskeleton device with the proposed control algorithm can significantly reduce the strain force of the wearerxe2x80x99s lumbar over 40% when they lift heavy loads. Thus it can improve the work efficiency of wearers and reduce their risk of lumbar diseases.