Kinematics analysis and gait planning for a hemiplegic exoskeleton robot

Background: As the world's aging population increases, the number of hemiplegic patients is increasing year by year. At present, in many countries with low medical level, there are not enough rehabilitation specialists. Due to the different condition of patients, the current rehabilitation training system cannot be applied to all patients. so that patients with hemiplegia cannot get effective rehabilitation training. Methods: Through a motion capture experiment, the mechanical design of the hip joint, knee joint and ankle joint was rationally optimized based on the movement data. Through the kinematic analysis of each joint of the hemiplegic exoskeleton robot, the kinematic relationship of each joint mechanism was obtained, and the kinematics analysis of the exoskeleton robot was performed using the Denavit-Hartenberg (D-H) method. The kinematics simulation of the robot was carried out in automatic dynamic analysis of mechanical systems (ADAMS), and the theoretical calculation results were compared with the simulation results to verify the correctness of the kinematics relationship. According to the exoskeleton kinematics model, a mirror teaching method of gait planning was proposed, allowing the affected leg to imitate the movement of the healthy leg with the help of an exoskeleton robot. Conclusions: A new hemiplegic exoskeleton robot designed by Shenzhen Institute of Advanced Technology (SIAT-H) is proposed, which is lightweight, modular and anthropomorphic. The kinematics of the robot have been analyzed, and a mirror training gait is proposed to enable the patient to form a natural walking posture. Finally, the wearable walking experiment further proves the feasibility of the structure and gait planning of the hemiplegic exoskeleton robot.

Structural Design, Simulation and Experiment of Quadruped Robot

This paper carried out a series of designs, simulations and implementations by using the physical-like mechanism of a bionic quadruped robot dog as a vehicle. Through an investigation of the walking mechanisms of quadrupeds, a bionic structure is proposed that is capable of omnidirectional movements and smooth motions. Furthermore, the kinematic and inverse kinematic solutions based on the DH method are explored to lay the foundation for the gait algorithm. Afterward, a classical compound pendulum equation is applied as the foot-end trajectory and inverse kinematic solutions are combined to complete the gait planning. With appropriate foot–ground contact modeling, MATLAB and ADAMS are used to simulate the dynamic behavior and the diagonal trot gait of the quadruped robot. Finally, the physical prototype is constructed, designed and debugged, and its performance is measured through real-world experiments. Results show that the quadruped robot is able to balance itself during trot motion, for both its pitch and roll attitude. The goal of this work is to provide an affordable yet comprehensive platform for novice researchers in the field to study the dynamics, contact modeling, gait planning and attitude control of quadruped robots.

Adaptive Walking Control for a Quadruped Robot on Irregular Terrain Using the Complex-Valued CPG Network

In this paper, we propose a CPG (central pattern generator) network control system using motor dynamics for the gait planning of a quadruped robot with a trot walking pattern to climb up and down a slope and turn back and follow the symmetry of route. The CPG unit model, which includes two DC motors model, has the ability to generate the periodic joint angle with complex-value parameters. Through plural feedback parameters, the CPG network can adjust the frequency and amplitude of an internal neuron model such as a robot meeting an irregular surface of a road. Using the stride length and frequency of robot joint angles, the distance of walking with a trot pattern can be calculated. In order to confirm the validity of the proposed control system, a quadruped robot is produced to implement the adaptive walking system.