Haptic assisted aircraft optimal assembly path planning scheme based on swarming and artificial potential field approach

• This paper presents a haptic guided framework (tool) for optimal assembly process.
• Swarm based optimization path planning scheme has been implemented for optimal assembly process.
• The scheme presented is then compared with existing technologies and the benefits of swarm based optimization are outlined.
• Virtual digital mockup based simulator is designed to test the effectiveness of the presented scheme.
• In addition the studies reviled that haptics implementation in the framework can further improve the engineering automation process.

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.