Autonomous Modular construction Using Drones, Opportunities and Challenges in Robotic construction

Using self-driving robots in construction could completely change the way things are done especially when ground robots and Unmanned Aerial Vehicles (UAVs) are coupled in mixed ways. This essay explores if such a hybrid system is viable, how it can be developed, and how it may be used in modular construction with an eye toward how well it would operate under demanding conditions. Ground robots move modules and operate as solar-powered charging stations, therefore helping with logistics; UAVs handle precise module placement. The main goal of the research is to find out how fast and how well this system can be expanded. It will mostly focus on how reinforcement learning (RL) could improve coordination and task assignment. The Construction world is modeled in this work using Rhinoceros and Grasshopper, running simulations of tasks including navigation and module alignment By allowing many agents to dynamically plan their trajectories, avoid collisions, and control their energy, RL algorithms facilitate the cooperation among several agents. While using opportunities to be more efficient, last longer, and be able to expand, the results reveal that the hybrid system does a decent job of handling significant issues including limited energy supply, environmental concerns, and the challenge of scheduling numerous tasks at once. Thanks to its modular construction of light, interlocking elements, the system is more adaptable in hostile or isolated locations such as disaster zones or extraterrestrial locales. This research prepares the stage for applying cutting-edge robotic systems in autonomous building, therefore enabling more affordable and ecologically friendly methods of construction.

کلیدواژه ها:

Modular Construction ، Autonomous Construction ، Reinforcement Learning (RL) ، Robotics ، UAVs