Multi-Objective Trajectory Planning for a Robotic Arm in Curtain Wall Installation

TL;DR

This paper introduces a multi-objective trajectory planning method for robotic arms in curtain wall installation, using an improved NSGA-III-FO algorithm to enhance efficiency and accuracy in complex construction environments.

Contribution

It proposes a novel multi-objective optimization algorithm with a focus operator, tailored for robotic arm trajectory planning in construction, demonstrating superior convergence and practical effectiveness.

Findings

NSGA-III-FO outperforms other algorithms in convergence speed.

The robotic arm design effectively handles complex curtain wall tasks.

Experimental results validate the algorithm's efficiency and practicality.

Abstract

In the context of labor shortages and rising costs, construction robots are regarded as the key to revolutionizing traditional construction methods and improving efficiency and quality in the construction industry. In order to ensure that construction robots can perform tasks efficiently and accurately in complex construction environments, traditional single-objective trajectory optimization methods are difficult to meet the complex requirements of the changing construction environment. Therefore, we propose a multi-objective trajectory optimization for the robotic arm used in the curtain wall installation. First, we design a robotic arm for curtain wall installation, integrating serial, parallel, and folding arm elements, while considering its physical properties and motion characteristics. In addition, this paper proposes an NSGA-III-FO algorithm (NSGA-III with Focused Operator, NSGA-III-FO) that incorporates a focus operator screening mechanism to accelerate the convergence of the algorithm towards the Pareto front, thereby effectively balancing the multi-objective constraints of construction robots. The proposed algorithm is tested against NSGA-III, MOEA/D, and MSOPS-II in ten consecutive trials on the DTLZ3 and WFG3 test functions, showing significantly better convergence efficiency than the other algorithms. Finally, we conduct two sets of experiments on the designed robotic arm platform, which confirm the efficiency and practicality of the NSGA-III-FO algorithm in solving multi-objective trajectory planning problems for curtain wall installation tasks.