This project aims to develop a swarm capable of uniform coverage and structural stability for tasks such as environmental monitoring, cleanup, and conservation, operating safely in cluttered or hazardous terrains. The goals which were achieved through this project are:
Maintain a triangular lattice for precise coverage
Dynamically avoid obstacles
Converge reliably to target locations
The Dynamic Swarm Robotics project implements a fully decentralised control strategy in which each robot maintains an equilateral triangular lattice while converging on a specified goal. Agents compute their motion using four local interaction forces—cohesion toward the swarm centroid, alignment toward the target, inter-robot repulsion, and obstacle avoidance—to ensure both formation stability and collision-free navigation. MATLAB-based simulations confirm that the triangular lattice persists even in cluttered environments, and that “virtual” obstacle agents enable robots to bypass barriers and seamlessly reform the lattice.
Performance metrics reveal robust navigation efficiency across different obstacle densities and consistently low computation latency per time step, validating the approach’s scalability and real-time applicability. This work provides a scalable foundation for extending decentralized swarm behaviors to more complex applications—such as environmental monitoring or dynamic area coverage—by combining simple, local sensing with elegant force-based control laws.
In this images it shows the connectivity analysis of each robot with it's swarm group which Indicates that at any moment each robot is connected to other members of the swarm group. Also the simulation is also mentioned here. Project repot and code in mention on the Github.
Find more detailed report here. 👉 Link