Path Planning for Manipulation Environments through Interpolated Walks

Manipulator robots working in changing environments need special path planners that provide good solutions in short times. In this work we describe a sample-based path planning algorithm that is suitable for such environments. Our approach is based on two points. Firstly, unlike most sampling techniques, we have defined a non-random local sampling which reduces the computational time greatly. Secondly, a set of interpolated walks is obtained through cubic splines which guarantee the smoothness and continuity of the walks. This path planning algorithm is part of a full intelligent manipulation system based on 3D vision