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.

This thesis investigates the integration of intelligent swarm robots as wall systems in the creation of automated architectural layouts tailored to user preferences, with a specific emphasis on ensuring spatial flexibility. The research seeks to address the challenges associated with accommodating swarm robots to create flexible architectural layouts while harnessing the adaptability and collective intelligence of swarm robotics. The study aims to contribute to the evolving field of user-centric architecture by exploring novel ways in which swarm robots can dynamically shape and customize spatial configurations to enhance comfort, user participation, and satisfaction.
The research methodology involves the development of a framework that combines principles of swarm intelligence, user-centric design, and flexible architecture. By leveraging swarm algorithms and self-organizing strategies, the swarm robots will be configured to respond to users’ preferences and needs and the evolving nature architectural space.

Insect pest elimination through MAV interception can reduce the need for insecticides and can contribute to sustainable agriculture. In this research, we analyze the feasibility of such solutions through simulated two-player differential games of pursuit and evasion with agents operating on minimalistic sets of biologically-plausible observations and optimized to control constrained vehicle models through deep multi-agent reinforcement learning. Our pursuer and evader agent, representing the quadcopter drone and insect pest respectively, are asymmetric in design, capabilities and objectives. Our results show that our quadcopter pursuer is consistently able to pursue and intercept a reactive insect-inspired evader as well as recordings of actual insect targets, achieving interception rates of 55% and 94% on these respective tasks. In comparison, pursuers alternatively optimized against non-reactive evaders or reactive drone-like evaders with symmetric capabilities, achieve an interception rate of only 42% for the same insect target recordings. Despite these promising results, we conclude that further research is needed to formally establish the superiority of multi-agent optimization in this asymmetric game scenario. Finally, we determine how emergent behavior and strategies resemble nature. During the confrontations, we observe that our pursuer mainly implements pure-pursuit as well as motion camouflage to some degree; drawing comparison to the hunting strategy of dragonfly.

This research project delves into the potentials of material jetting printing through an exploration of voxel printing techniques that integrate solids and liquids. The focus centers on assessing the shock absorption (SA) capabilities of diverse samples incorporating varying materials and printing patterns. The key materials employed in this investigation comprise Agilus, a flexible substance, and Veroclear, a rigid material. The project advances through multiple phases, commencing with an extensive literature review and culminating in the successful fabrication of a range of varied samples.

The research objectives encompass two main aspects. Firstly, the goal is to generate a series of test samples characterized by distinct attributes, facilitating a comprehensive evaluation of their shock absorption abilities. This entails manipulating factors like material composition and printing patterns to yield a diverse array of samples. Secondly, leveraging the test outcomes, the aim is to conceptualize a product that effectively demonstrates the potential of material printing technology. This product will exemplify optimized shock absorption characteristics, serving as a tangible illustration of the technology’s possible applications. In this design process, the diverse assortment of test samples and their individual traits are considered, leveraging these findings to craft an inventive and practical wearable product.

The realization of these objectives initiates with an understanding of a material printing apparatus equipped for voxel printing. Thorough research is undertaken to amass pertinent information concerning voxel printing methods, material attributes, and shock absorption principles. Armed with a solid knowledge foundation, the project progresses to the printing phase, wherein an array of samples is produced employing rigid, flexible, and liquid materials. Meticulous attention is dedicated to selecting printing patterns, enabling a comprehensive exploration of the impact of different geometries on shock absorption.

The subsequent stage encompasses subjecting the printed samples to controlled shock tests. This examination aims to discern patterns, correlations, and trends that can inform future design choices. Drawing from these findings, a proposal outlining future projects capitalizing on voxel printing technology is formulated. This proposal takes the form of a conceptual project designed to effectively showcase the material’s capabilities. Ultimately, this research endeavors to stimulate the development of ingenious and efficacious applications of voxel printing, thereby contributing to the advancement of materials engineering and product design domains, exemplified through a conceptual wearable product that serves as a reference for the potential utilization of the technology.

Automation in the form of swarm robots is an increasingly feasible opportunity for solving complex physical problems. However, how such a swarm is to be instructed and controlled is one of the many topics that requires further research. For this, we can look to nature for inspiration, as there are many nest building swarms. Perhaps the most notable of which are the mound building termites. These termites build incredibly intricate mounds that contain a royal chamber, nurseries, fungal gardens, covered walkways, and even ventilation shafts to thermoregulate the inside of the mound. There are some attempts to capture this behaviour in custom simulators. The problem is that these simulators have limited capabilities. That is why a new simulator specifically for termite-like builder robot swarms is required for further research in this field. In this project, the different requirements for such a simulator are identified and used to develop an open-source state of the art simulator, TermiteSim. TermiteSim is designed for experimenting with different control strategies and tuning the simulation parameters to recreate the desired behaviour. In other words: a tool for researchers to design desired behaviour of a builder robot swarm. In this thesis TermiteSim is used to simulate several termite-like building behaviours described in the literature and the resulting structures are compared to those of other simulators, which TermiteSim was successfully able to recreate.