The attitude motion planning for one-legged hopping robot with nonholonomic constraint is studied. Firstly, the dynamic model of the robot is established by using the nonholonomic constraint characteristic. Secondly, the energy consumption of the robot is used as the optimization objective function. Lastly, a numerical algorithm is designed by combining curve fitting method and particle swarm optimization algorithm, which is used to realize the optimal trail of robot’s attitude motion by optimizing the objective function. The designed algorithm makes use of curve fitting to approach the motion trail of the robot’s drivable leg, and the coefficients of the fitting polynomial are taken as the optimization parameters which can be obtained by particle swarm optimization algorithm. The main advantage of this method lies in that the initial value and the final value of the optimal control input are all zero, which solves the problem that the initial value and the final value of the control input are not zero in the traditional method, making it convenient to control the motion of the drivable leg by the motor in engineering application. At the end of the study, the effectiveness of this method is proved by the results of the numerical simulation.
one-legged hopping robot, nonholonomic constraint, attitude motion planning, optimization
This work was supported by Zibo science and technology development plan (2016kj010057).
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