CAD2VR or How to Efficiently Integrate VR into the Product Development Process
CAD 2002: Corporate Engineering Research
Virtual disassembly of products based on geometric models
Computers in Industry
Assembly planning based on semantic modeling approach
Computers in Industry
A discrete version of particle swarm optimization for flowshop scheduling problems
Computers and Operations Research
Applications of particle swarm optimisation in integrated process planning and scheduling
Robotics and Computer-Integrated Manufacturing
A haptic-based approach to virtual training for aerospace industry
Journal of Visual Languages and Computing
Robotics and Computer-Integrated Manufacturing
Hi-index | 0.00 |
In this research, a novel near optimum automated rigid aircraft engine parts assembly path planning algorithm based on particle swarm optimization approach is proposed to solve the obstacle free assembly path planning process in a 3d haptic assisted environment. 3d path planning using valid assembly sequence information was optimized by combining particle swarm optimization algorithm enhanced by the potential field path planning concepts. Furthermore, the presented approach was compared with traditional particle swarm optimization algorithm (PSO), ant colony optimization algorithm (ACO) and genetic algorithm (CGA). Simulation results showed that the proposed algorithm has faster convergence rate towards the optimal solution and less computation time when compared with existing algorithms based on genetics and ant colony approach. To confirm the optimality of the proposed algorithm, it was further experimented in a haptic guided environment, where the users were assisted with haptic active guidance feature to perform the process opting the optimized assembly path. It was observed that the haptic guidance feature further reduced the overall task completion time.