Calibration of Modular Reconfigurable Robots Based on a Hybrid Search Method

Author:

Lin Yu1,Xi Fengfeng1,Mohamed Richard Phillip1,Tu Xiao-wei2

Affiliation:

1. Department of Aerospace Engineering, Ryerson University, Toronto, ON, M5B 2K3, Canada

2. Department of Aerospace Engineering, Ryerson University, Toronto, ON, M5B 2K3, Canada; Aerospace Manufacturing Technology Center, National Research Council Canada, Montreal, QC, H3T 2B2, Canada

Abstract

Developed in this paper is a hybrid method for calibration of modular reconfigurable robots (MRRs). The underlying problem under study is unique to MRRs, that is, how to calibrate a set of MRR’s geometric parameters that are applicable to all feasible configurations. For this reason, a hybrid search method is developed to ensure a global search over the MRRs’ workspace for each feasible configuration. By combining a genetic algorithm method with a Monte Carlo method, this method includes three levels of search, namely, pose, workspace, and configuration-space. The final set of global solutions is generated progressively from the results of these three levels of search. The effectiveness of this method is demonstrated through a case study.

Publisher

ASME International

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Control and Systems Engineering

Reference28 articles.

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