Dynamic modeling and configuration adaptive control for modular reconfigurable robot

Xiaofeng Wang,Weimin Ge,Jun Liu,Minglu Zhang

doi:10.1177/1687814017726005

Xiaofeng Wang, Weimin Ge + Show 2 more

Open Access

https://doi.org/10.1177/1687814017726005

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Abstract

A unit module of the mobile modular reconfigurable robot (M2rBot) with the 12 connection ways is first introduced. For expressing the spatial connection relations and the traversing paths of the M2...

Highlights

Modular reconfigurable robot (MRR), composed of multiple modular components, is a variable topology system that can manually rearrange the modules’ connectedness and form a large variety of robot configurations
The dynamics equations based on Newton–Euler method are simple, fast, and precise, but the forward and inverse recursive equations destroy the whole structure of the dynamics model, so it is difficult to design the compensation controller
For the M2rbot, the kinematics starts with a two-module assembly model and a spatial connection matrix (SCM) representation

Summary

Introduction

Modular reconfigurable robot (MRR), composed of multiple modular components, is a variable topology system that can manually rearrange the modules’ connectedness and form a large variety of robot configurations. The dynamics equations based on Newton–Euler method are simple, fast, and precise, but the forward and inverse recursive equations destroy the whole structure of the dynamics model, so it is difficult to design the compensation controller. For the MRR, the compensatory controller is designed for compensating uncertainties of one fixed-configuration model and for adapting to the dynamics models with different configurations. Inspired by the work from Chen and Yang, the kinematic and dynamics equations for multiple branches are derived by the recursive method with a more simple expression of spatial connection relationships among the modules. For the M2rbot, the following characteristics are considered: the simple module structure which can move independently, the rich connecting surfaces and connecting ports, and the reliable locking mechanism. For the M2rbot, the kinematics starts with a two-module assembly model and a spatial connection matrix (SCM) representation. The forward kinematic transformations for the path k with m branches, based on the dyad kinematics, can be formulated as follows

G1 3 2

Conclusion