Kinematics Solving of Under-constrained Cable-driven Parallel Robots Based on Intelligent Algorithm

Abstract

The under-constrained cable-driven parallel robots is a special kind of robot that uses cables instead of traditional rigid links to control the end effector, and its typical character is that the number of cables is less than the number of freedoms. Both the geometric and static equilibrium equations of the under-constrained mechanism are coupled to each other, which brings great difficulties to solve the kinematics problems. In this paper, an improved particle swarm intelligence algorithm is proposed. By introducing the simulated annealing idea and the adaptive weight factor, the positive kinematics and inverse kinematics problems of the under-constrained cable-driven parallel robots are solved. Finally, under-constrained cable-driven parallel robots with three cables and four cables are taken as examples to carry out numerical simulation. The final results show that the intelligent algorithm is effective and feasible, and can provide theoretical guidance for the design of subsequent under-constrained parallel robots.