Optimizing Task Scheduling for Efficient and Ergonomic Human-Robot Collaboration in Construction Tasks

Abstract

Human-robot collaboration (HRC) offers transformative potential for construction to mitigate labor shortages and enhance productivity. Effective task scheduling between human workers and robots is essential for maximizing productivity while reducing workloads of human workers. Extensive research focusing on either task sequencing or work-rest scheduling, which often neglects the interdependence between these two components, leading to suboptimal performance of overall team. Additionally, the existing literature on task scheduling in HRC scenarios within construction is limited, particularly regarding the integration of the dynamic behavior of human and superior physical capabilities of robots. Research gaps remain in coupling task sequencing and work-rest scheduling, as well as in considering the distinct capabilities of human and robot agents.

This study proposes an approach that integrates work-rest scheduling with task sequencing by incorporating rest periods as a special task within the optimization process. The proposed method employs a multi-objective genetic algorithm (GA) to maximize work output, robot utilization, and minimize human fatigue, while considering dynamic worker productivity. Additionally, the framework is designed to reschedule tasks in response to the dynamic behaviors of human workers. Experimental results validate the effectiveness of the proposed method in enhancing productivity and reducing human fatigue. This improvement exceeds 10% when compared to existing studies that separate work-rest scheduling from task sequencing. The dynamic scheduling capabilities in adapting to human flexible actions are also verified in comparison to predefined scheduling.

Date of Award	2025
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology
Supervisor	Yantao YU (Supervisor)