Dynamic modeling and crawling gait control of six-strut spherical tensegrity robot

In this paper, the crawling gait control of a six-strut spherical tensegrity robot is studied. The dynamic model of the robot is established by Newton-Euler equations, and the numerical simulations are constructed in MATLAB. The correctness of numerical simulation is verified by using ADAMS simulation software. Next, the motion mechanism of the crawling gait is considered, and parameters such as gravity cone and gravity moment are introduced, the initial configuration, active cables and driving parameters range suitable for robot crawling gait are obtained. Taking the maximum distance moved by the robot in a certain direction as the optimization objective, the problem of controlling the crawling gait is transformed into an optimization problem, and the particle swarm optimization algorithm is used to optimize the driving parameters of the crawling gait. The motion performance of the robot is evaluated by three indicators: motion velocity, driving energy consumption, and moving direction deviation. Two methods for optimizing the motion performance are proposed. Finally, an experimental platform is set up to carry out the crawling gait experiment and verify the above methods. The research results can provide technical support for further engineering applications of the six-strut spherical tensegrity robot.