Enhancing Autonomy on Construction Sites through Implementation of Swarm Robotics as adaptive Material-Handling logistics system

Master thesis (2024)

Authors

Z.K. Khoshnevis Architecture and the Built Environment

Contributors

Serdar Așut Digital Technologies (mentor)
Stijn Brancart Architectural Technology (graduation committee member)
Jordan H. Boyle Emerging Materials (graduation committee member)
Faculty
Architecture and the Built Environment, Architecture and the Built Environment
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Published Date

03-07-2024

Language

English

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Faculty

Architecture and the Built Environment

Abstract

This thesis explores the application of swarm robotics in addressing construction sites' dynamic and complex challenges by using them as material handling units. Despite significant technological advances, the construction industry continues to face substantial challenges related to the human workforce, including skilled labor shortages, high safety risks, and inefficient communication, all of which impede productivity and safety. Swarm robotics, inspired by the decentralized behaviors of social insects, offers a promising solution to these issues by enabling distributed task management and enhanced flexibility and robustness in dynamic environments.

The research specifically investigates the implementation of swarm robotics as an adaptive on-site logistics system for dynamic construction sites. Using Ant Colony Optimization, a path-planning swarm intelligence-based algorithm derived from the foraging behavior of ants, this study examines the algorithm’s applicability for enhancing material handling within the unpredictable conditions of construction sites. The study includes the development of an architectural scenario for a virtual simulation environment and practical experiments on two different architectural scenarios to evaluate the effectiveness of swarm robotics in real construction scenarios.

This study demonstrates the advantages of decentralized control in swarm robotics for enhancing operational efficiency, reducing safety risks, and improving communication on construction sites. The outcomes include the development of a Design-to-Construction workflow using a scalable and resilient construction logistics system that takes advantage of the unique capabilities of swarm robotics. This outcome has the potential to revolutionize construction practices through the integration of advanced robotic technologies and decentralized management systems.

Additionally, virtual experiments as part of the workflow indicate that achieving optimal values for parameters in the simulation, such as the required number of robots and pheromone evaporation rate, is highly scenario-dependent. This conclusion highlights the necessity of using the developed workflow that enables designers and construction groups to create their desired architectural layouts, simulate their construction process, and optimize them for further construction using swarm robots, effectively bridging the gap from initial design to final construction.