Cartesian trajectory planning of a free-floating space robot is impacted by dynamic singularities due to the inverse kinematics equations. Although various methods have been proposed to avoid the singularities, very few of them are suitable for the trajectory planning of a high degree-of-freedom (DOF) space robot in the Cartesian space. In this paper, a method of combining Damped Least Squares (DLS) and feedback compensation is developed to avoid such singularities. The trajectories of the end-effector are parametrized with Bézier curves, which are simple and make it easy to limit the joint velocities. Moreover, because of certain missions, such as communication and observation, base attitude disturbance and moving time are considered to establish a cost function and the trajectory planning is transformed into a multi-objective optimization. Chaotic particle swarm optimization (CPSO) is employed to solve the optimization, which can improve the premature phenomenon of particle swarm optimization (PSO). Simulation results are presented for the trajectory planning of a 6 DOF space robot and demonstrate the effectiveness of the proposed method.

Cartesian trajectory planning of space robots using a multi-objective optimization

Rocco P.;
2021-01-01

Abstract

Cartesian trajectory planning of a free-floating space robot is impacted by dynamic singularities due to the inverse kinematics equations. Although various methods have been proposed to avoid the singularities, very few of them are suitable for the trajectory planning of a high degree-of-freedom (DOF) space robot in the Cartesian space. In this paper, a method of combining Damped Least Squares (DLS) and feedback compensation is developed to avoid such singularities. The trajectories of the end-effector are parametrized with Bézier curves, which are simple and make it easy to limit the joint velocities. Moreover, because of certain missions, such as communication and observation, base attitude disturbance and moving time are considered to establish a cost function and the trajectory planning is transformed into a multi-objective optimization. Chaotic particle swarm optimization (CPSO) is employed to solve the optimization, which can improve the premature phenomenon of particle swarm optimization (PSO). Simulation results are presented for the trajectory planning of a 6 DOF space robot and demonstrate the effectiveness of the proposed method.
2021
Base attitude disturbance
CPSO
Dynamic singularities
Space robot
Trajectory planning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1164730
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