Geometrically constrained path planning for robotic grasping with Differential Evolution and Fast Marching Square

Abstract

This paper presents a new approach for geometrically constrained path planning applied to the field of robotic grasping. The method proposed in this paper is based on the Fast Marching Square (FM $\, ^2$ ) and a path calculation approach based on an optimization evolutionary filter named Differential Evolution (DE). The geometric restrictions caused by the link lengths of the kinematic chain composed by the robot arm and hand are introduced in the path calculation phase. This phase uses both the funnel potential of the surroundings created with FM $\, ^2$ and the kinematic constraints of the robot as cost functions to be minimized by the evolutionary filter. The use of an optimization filter allows for a near-optimal solution that satisfies the kinematic restrictions, while preserving the characteristics of a path computed with FM $\, ^2$ . The proposed method is tested in a simulation using a robot composed by a mobile base with two arms.

A comprehensive review of the latest path planning developments for multi-robot formation systems

“…In ref. [62], the fingers of an end effector of a manipulator were treated as stand-alone robots. Therefore, a leader–follower approach based on was implemented on UR3 robot to achieve grasping application.…”

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“…In dealing with interactions between the robot's end-effector or platform's tool and the environment, the fourth paper of this special issue by Muñoz, López et al presents a new approach to geometrically constrained path planning for robotic grasping using fast marching square (FM 2 ) and differential evolution (DE) techniques [4]. For this, geometrical constraints imposed by the robot arm and hand are coded in some cost functions correspondingly for the optimization purpose.…”

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