Unmanned Transport System using SWARM Bots

Abstract

The Internet of Things (IoT) is revolutionizing transportation, with the market surging from $135 billion USD in 2016. This growth highlights the integration of IoT devices, robotics, and automation, enhancing efficiency across various sectors. Robotics-based IoT merges robotics with IoT, enabling real-time communication and autonomous decision-making through sensor networks. In manufacturing, IoT-enabled robots optimize production by monitoring equipment health, predicting maintenance, and streamlining workflows, reducing downtime, and increasing productivity. In healthcare, robotic systems enhance patient care by monitoring vitals, administering medications, and performing precise surgeries, all while communicating with healthcare providers for coordinated care. The logistics sector benefits from autonomous drones and vehicles that optimize routes and manage inventory efficiently, ensuring timely deliveries and reducing human error. Keeping all these in contentions, Swarm robotics based unmanned transportation system using collaborative robots (ColBots), was conceived in this paper. Swarm robots are inspired by ant colonies, involving multiple wirelessly connected robots, communicating seamlessly, in an coordinated actions. This technology enables efficient teamwork for tasks like cleaning, assembly, and exploration of hazardous environments. Following this view, the following research work explores unmanned transport systems using swarm bots, highlighting the interaction between humans and robotics. The solution explores the concept of master and slave configuration pattern in order to boost the overlapping communication protocol. Using LiDAR as the main data actuation tool for automated navigation, a prototypic exploration on the same has been made to solve of generic tasks via the ColBots. The results suggests that this protype is capable enough to be used for most of general transportation services and can help in transportation on any scale whether be it inside a building or inside a city or across states.