Title :
Nuero-fuzzy multi-objective trajectory planning of redundant manipulators
Author :
Khoukhi, Amar ; Demirli, Kudret ; Baron, Luc ; Balazinski, Marek
Author_Institution :
Univ. of Montreal, Montreal
Abstract :
In this paper, the problem of multi-objective trajectory planning is studied for redundant planar serial manipulators using a data-driven hybrid neuro-fuzzy system. A first pre-processing step involves an offline planning generating a large dataset of multi-objective trajectories, covering mostly the robot workspace. The optimized criteria are travelling time, consumed energy, and singularity avoidance. The offline planning is initialized through a cycloidal minimum time parameterized trajectory in joint space. This trajectory is then optimized using an augmented Lagrangian technique. The outcomes of this pre-processing step allow building a Tsukamoto neuro-fuzzy inference system to learn and capture the robot multi-objective dynamic behavior. Once this system is trained and optimized, it is used in a generalization phase to achieve online planning. Simulation results showing the effectiveness of the proposal are presented and discussed.
Keywords :
fuzzy neural nets; fuzzy reasoning; path planning; redundant manipulators; Tsukamoto neuro-fuzzy inference system; augmented Lagrangian technique; cycloidal minimum time parameterized trajectory; neuro-fuzzy multiobjective trajectory planning; offline planning; redundant manipulators; robot workspace; Control systems; Fuzzy neural networks; Gain; Manipulator dynamics; Motion planning; Optimal control; Orbital robotics; Robots; Torque; Trajectory;
Conference_Titel :
Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
978-1-4244-0990-7
Electronic_ISBN :
978-1-4244-0991-4
DOI :
10.1109/ICSMC.2007.4414164