Stitching Dynamic Movement Primitives and Image-based Visual Servo Control

TL;DR

This paper introduces a unified control scheme that switches between Dynamic Movement Primitives and Image-based Visual Servo control, enabling robust robot end-effector motion in tasks with changing visual information.

Contribution

It proposes a generalized switching control framework with a common state space for DMPs and IBVS, including stability analysis and real-world validation.

Findings

The control scheme ensures convergence to a bounded state.

Experimental validation on a Baxter robot demonstrates effectiveness.

Stability analysis confirms asymptotic convergence of the switched system.

Abstract

Utilizing perception for feedback control in combination with Dynamic Movement Primitive (DMP)-based motion generation for a robot's end-effector control is a useful solution for many robotic manufacturing tasks. For instance, while performing an insertion task when the hole or the recipient part is not visible in the eye-in-hand camera, a learning-based movement primitive method can be used to generate the end-effector path. Once the recipient part is in the field of view (FOV), Image-based Visual Servo (IBVS) can be used to control the motion of the robot. Inspired by such applications, this paper presents a generalized control scheme that switches between motion generation using DMPs and IBVS control. To facilitate the design, a common state space representation for the DMP and the IBVS systems is first established. Stability analysis of the switched system using multiple Lyapunov functions shows that the state trajectories converge to a bound asymptotically. The developed method is validated by two real world experiments using the eye-in-hand configuration on a Baxter research robot.