Task planning for human-robot collaboration in structure assembly

Abstract

Integrating robotics in construction works has the potential to address persistent challenges such as labor shortages, health risks, and low productivity. This paper proposes a systematic task planning approach for human-robot collaboration (HRC) in structure assembly, comprising a robotic potential scoring-based task classification system and a constraint programming-based task allocation and sequencing optimization model. Based on key factors such as component properties, connection methods, robotic payload capacities, material storage layouts, and workspace safety, the task classification system provides a systematic approach to classifying construction tasks. To obtain optimal task allocation and sequencing, an extended flexible job shop scheduling problem (FJSSP) based optimization model integrates human fatigue into the objective function to balance operational efficiency and worker well-being. A timber frame assembly case study with different HRC configurations and storage arrangements was conducted to evaluate the performance in enhancing makespan and reducing human fatigue. This work establishes a robust foundation for optimizing HRC in structure assembly, paving the way for more effective and human-centric practices in the industry.