Trajectory Planning of Aerial Robotic Manipulator Using Hybrid Particle Swarm Optimization

Abstract

The trajectory planning of an aerial robotic manipulator system is studied using Hybrid Particle Swarm Optimization (HPSO). The aerial robotic manipulator is composed of an unmanned aerial vehicle (UAV) base and a robotic manipulator. The robotic manipulator is dynamically singular. In addition, strong coupling exists between the UAV base and the robotic manipulator. To overcome the problems, the trajectory planning is studied in the join space using HPSO. HPSO combines superiorities of PSO and GA (Genetic Algorithm), prohibiting particles from becoming trapped in a local minimum. In addition, the control parameters are self-adaptive and contribute to fast searching for the global optimum. The trajectory planning problem is converted into a parameter optimization problem. Each joint trajectory is parameterized with a Bézier curve. The HPSO is implemented to optimize joint trajectories, satisfying specific objectives and imposed constraints. Numerical simulations are also carried out to validate the effectiveness of the proposed method.