This paper presents the E-LEG, a novel semi-passive lower-limb exoskeleton for worker squatting assistance, with motorized tuning of the assistive squatting height. Compared with other passive industrial exoskeletons for the lower-limbs, the E-LEG presents novel design features namely inertial sensor for measuring the tilt angle of thigh and the novel electromagnetic switch for adjusting squat height. These features could enhance the effectiveness of the system. In addition to the introduction to exoskeleton design, this paper also reports the systematic experimental evaluation of human subjects. With the assistance of different conditions, the variability of muscular activity was evaluated in long-term static squatting task. The set of metrics to evaluate the effect of the device included leg muscle activity, plantar pressure fluctuation, plantar pressure center fluctuation and gait angles. Results show that the exoskeleton can reduce the muscular activity of the user during squatting, and it will have little affect the normal gait of the user during walking. In this study, we found that the E-LEG exoskeleton has potential effectiveness in reducing the muscular strain on long-term continuous squatting activities.

This study designs and controls an active stabilizing assistant system (ASAS) for a bicycle. Using the gyroscopic effect of two spinning flywheels, the ASAS generates torques that assist the rider to stabilize the bicycle in various riding modes. Riding performance and the rider’s safety are improved. To simulate the system dynamic behavior, a model of a bicycle–rider system with the ASAS on the rear seat is developed. This model has 14 degrees of freedom and is derived using Lagrange equations. In order to evaluate the efficacy of the ASAS in interacting with the rider’s control actions, simulations of the bicycle–rider system with the ASAS are conducted. The results for the same rider for the bicycle with an ASAS and on a traditional bicycle are compared for various riding conditions. In three cases of simulation for different riding conditions, the bicycle with the proposed ASAS handles better, with fewer control actions being required than for a traditional bicycle.

The restoration of walking capability is very important after central nervous system (CNS) injury. Rehabilitation training robot can replace therapists to help patients do walking training by accurately simulating the human lower limb movement, and achieve the purpose of rehabilitation ultimately. In order to further improve the rehabilitation robots' intelligent and rehabilitation training effect and completely replace therapists to some extent, a new design method is proposed in this paper: firstly, the pleasant mechanical structure design method for the rehabilitation robot is put forward. Then, the rehabilitation robot's perceptual system is designed, which includes the detection methods of bioelectric and physical signals and the effective integration of the sensor network based on multi-agent system are presented. Finally, the superiority of the rehabilitation robot designed in this paper is described through results analysis.

Motorcycles are widely used in people’s daily lives for their convenience. Due to their characteristic of static instability, they have a larger roll angle than cars when turning, which brings the hidden danger of overturning. When a motorcycle is turning and braking simultaneously, the overturn risk rises dramatically. This study presents a novel control system that can ensure stability and braking performance during turning and braking. Given the direct impact of tires on a motorcycle’s behavior, a motorcycle tire model was created via Magic Formula to determine the kinematic parameters that have correlated effects on the longitudinal and lateral characteristics of tires. The slip ratio was defined as the manipulated variable, and a constrained optimization model that aimed to maximize the braking performance and took the stability as the constraint condition was created and solved through the gold section method. The obtained optimal slip ratio was then used as the input for the proposed cornering braking control system that adopted the Fuzzy PID algorithm. Finally, the feasibility of the proposed controller was tested via a co-simulation method, and the simulation results were compared with an ordinary anti-lock braking system. The results demonstrate that the proposed cornering braking control system can take both motorcycle stability and braking performance into consideration at the same time, effectively increasing the security of a motorcycle during braking in a turn.

This study determines the roll angle for a two-wheeled single-track vehicle during cornering. The kinematics are analyzed by coordinate transformation to determine the relationship between the measured acceleration and the acceleration in the global coordinate. For a measurement error or noise, the state space expression is derived. Using the theory for a Kalman filter, an estimator with two-step measurement updates estimates the yaw rate and roll angle using the acceleration and angular velocity signals from an IMU sensor. A bicycle with relevant electronic products is used as the experimental object for a steady turn, a double lane change and a sine wave turn in real time to determine the effectiveness of the estimator. The results show that the proposed estimator features perfect reliability and accuracy and properly estimates the roll angle for a two-wheeled vehicle using IMU and velocity.