Trajectories Planning in Presence of Obstacles for Manipulator Robots

Abstract

The problem of trajectories planning for manipulator robots in workspaces clustered with static obstacles is described as NP-hard. This pushed many researchers to adopt simplifying assumptions and consequently, to develop resolution methods dedicated to particular cases. In this article, we propose a general methodology, which deals with the problem by taking into account a large range of imposed constraints. The suggested methodology consists, initially, on finding a collision-free path connecting the initial to the final position, from a roadmap built offline, in a random way in the free C-space of the robot. Finally, the found path is injected into a stochastic optimization procedure based on cubic splines.