In order to judge and control applied force of Chinese massage robot’s end-effector on human body accurately, multi-dimensional interactive forces between massage robot’s end-effector and human should be measured. In this paper, a novel two-axis force sensor suitable for massage robot’s end-effector is presented, which is much smaller than existing sensors but in the same range measurement. Mechanical structure is introduced, theoretical analysis of elastic body is made, and finite element analysis is used to analyze its static characteristic. Then, the distribution of strain gauges and design of Hilton Bridge Circuit are described in detail. Finally, a prototype is fabricated. Decoupling algorithm is designed to reduce the interference error. The result of static calibration experimental data shows that the sensor has features of high precision and sensitivity.

In the effort to make robot-assisted upper limb passive movement training effective for neurologic injuries suffered from stroke and spinal cord injury (SCI), a new fuzzy adaptive closed-loop supervisory control method for passive joint movement training is proposed. Firstly, high-level supervisory controller for the desired passive range of motion (PROM) is designed based on the impaired limb’s joint motion recovery, and then low-level closed-loop position tracking controller is presented to drive the robot stably and smoothly to stretch the impaired limb to move along the predefined trajectory. The suggested strategy was applied to the four degrees of freedom (DOF) Whole Arm Manipulator (WAM) rehabilitation robot to evaluate its performance. Experimental results carried out on the 4-DOF WAM rehabilitation robot show the effectiveness and potentialities of the fuzzy adaptive passive movement control in clinical application.

An algorithm based on the differential evolutionary (DE) computation is proposed to evaluate circularity error. It is a heuristic evolutionary algorithm based on population optimization .In the meantime, the suggested method is used to solve the minimum zone circularity error. Compared with other methods, the results show the presented method has very strong self-adaptive ability to environment and better global convergence. Examples proves that the proposed method is effective, convergence and robustness in the process of optimization. And this method makes the circularity error evaluation more accurate.

Sampled-data system’s nature is the main factor that causes virtual wall to demonstrate active (non-passive) behavior, destroying the illusion of reality. To enhance the stability of haptic rendering by virtual wall model, a novel spring-impulse model based on energy conversation and momentum conversation is proposed. In the model, an impulse in the opposite direction of avatar’s velocity is exerted on avatar at the instant from inner of virtual wall back to balance position during unstable state. This resistant forces eliminate extra work to reduce the non-passive behaviors of the haptic system, which lead to improved realistic rigid perceptions and system stability. The experiments have verified the effectiveness of our spring-impulse method in a virtual stiff-wall prototype system via a Phantom Omni haptic device.