In dynamic manufacturing and warehousing environments, the work scene made it impossible for workers to sit, so workers suffer from muscle fatigue of the lower limb caused by standing or squatting for a long period of time. In this paper, a semi-active exoskeleton used to reduce the muscle fatigue of the lower limb was designed and evaluated. (i) Background: The advantages and disadvantages of assistive exoskeletons developed for industrial purposes were introduced. (ii) Simulation: The process of squatting was simulated in the AnyBody.7.1 software, the result showed that muscle activity of the gluteus maximus, rectus femoris, vastus medialis, vastus lateralis, vastus intermedius, and erector spinae increased with increasing of knee flexion angle. (iii) Design: The exoskeleton was designed with three working modes: rigid-support mode, elastic-support mode and follow mode. Rigid-support mode was suitable for scenes where the squatting posture is stable, while elastic-support mode was beneficial for working environments where the height of squatting varied frequently.The working environments were identified intelligently based on the EMGs of the gluteus maximus, and quadriceps, and the motor was controlled to switch the working mode between rigid-support mode and elastic-support mode. In follow mode, the exoskeleton moves freely with users without interfering with activities such as walking, ascending and descending stairs. (iv) Experiments: Three sets of experiments were conducted to evaluate the effect of exoskeleton. Experiment one was conducted to measure the surface electromyography signal (EMGs) in both condition of with and without exoskeleton, the root mean square of EMGs amplitude of soleus, vastus lateralis, vastus medialis, gastrocnemius, vastus intermedius, rectus femoris, gluteus maximus, and erector spinae were reduced by 98.5, 97.89, 80.09, 77.27, 96.73, 94.17, 70.71, and 36.32%, respectively, with the assistance of the exoskeleton. The purpose of experiment two was aimed to measure the plantar pressure with and without exoskeleton. With exoskeleton, the percentage of weight through subject's feet was reduced by 63.94, 64.52, and 65.61% respectively at 60°, 90°, and 120° of knee flexion angle, compared to the condition of without exoskeleton. Experiment three was purposed to measure the metabolic cost at a speed of 4 and 5 km/h with and without exoskeleton. Experiment results showed that the average additional metabolic cost introduced by exoskeleton was 2.525 and 2.85%. It indicated that the exoskeleton would not interfere with the movement of the wearer Seriously in follow mode. (v) Conclusion: The exoskeleton not only effectively reduced muscle fatigue, but also avoided interfering with the free movement of the wearer.

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For a mobile robot, navigation skills that are safe, efficient, and socially compliant in crowded, dynamic environments are essential. This is a particularly challenging problem as it requires the robot to accurately predict pedestrians' movements, analyse developing traffic situations, and plan its own path or trajectory accordingly. Previous approaches still exhibit low accuracy for pedestrian trajectory prediction, and they are prone to generate infeasible trajectories under complex crowded conditions. In this paper, we develop an improved socially conscious model to learn and predict a pedestrian's future trajectory. To generate more efficient and safer trajectories in a changing crowed space, an online path planning algorithm considering pedestrians' predicted movements and the feasibility of the candidate trajectories is proposed. Then, multiple traffic states are defined to guide the robot finding the optimal navigation strategies under changing traffic situations in a crowded area. We have demonstrated the performance of our approach outperforms state-of-the-art approaches with public datasets, in low-density and simulated medium-density crowded scenarios. and then predicted the position and velocity of humans for a finite horizon. Schulz et al. [6] combined pedestrian intention recognition with path prediction, through an interacting multiple model filter in combination with a latent-dynamic conditional random field model. However, most of these research works are limited by independent models that fail to capture the complex interactions between the humans in the crowd. An alternative and recent method utilizes learning techniques to model the joint distribution of future trajectories of interacting agents based on a spatially local interaction model. Trautman et al. [7] proposed an interactive Gaussian process approach, whose kernels were used to model human dynamics, to capture cooperative collision avoidance between humans and a robot. Alahi et al. [8] proposed long-short term memory (LSTM) networks with "social" pooling layers, which learned general human movements and predicted their future trajectories. Recently, we proposed a socially conscious model considering the added features that affect the pedestrian's future trajectory, such as the walking direction of other pedestrians [9]. However, these approaches do not carefully distinguish the effects of a pedestrian's own history trajectory, and that of others, to the pedestrian's future trajectory, and this may hinder the improvement of model accuracy.Developing efficient online path planning algorithms to generate robots' safe and smooth trajectory is a basic problem in robot navigation. Safe trajectory generation is a very active field in mobile robotics and there are many recent contributions. Ravankar [10] and David [11] reviewed the state-of-the-art in smooth trajectory generation with comparisons in terms of kinematic feasibility and safe path generation recently. Additionally, the approaches that are available with robot operating system ...

This paper studies the thermoelastic dynamic response of a simply supported beam under movable temporally non-Gaussian laser pulse. The heat conduction equation of the problem was solved by using the method of separation of variables. The Green’s function for the forth-order partial differential equation was derived and was used to solve the vibration equation of a heated beam. The temperature, deflection, and strain of the beam were derived analytically and their variations with time and space were illustrated. The influences of moving speed and duration time of the laser pulse on the dynamic responses were also analyzed. It was interesting to observe the propagation of strain wave along the beam axis during the irradiation period of the laser pulse.