Swarm Intelligence & Analytics
Inspired by biology, powered by mathematics — DISAL's flagship research area designs scalable decentralised algorithms for drone fleets, smart grids, and complex system optimisation.
Swarm Intelligence & Analytics
Drawing inspiration from ant colonies, bird flocks, and fish schools, our swarm intelligence research builds algorithms that solve complex optimisation problems through collective emergent behaviour. Applications range from multi-UAV coordination and smart-grid load balancing to logistics and disaster-response robotics.
Key Research Topics
Multi-UAV Coordination
Decentralised formation control, task allocation, and collision avoidance for heterogeneous drone swarms in GPS-denied environments.
Swarm Optimisation Algorithms
Bio-inspired algorithms — PSO, ACO, Bee Algorithms — applied to NP-hard combinatorial and continuous optimisation problems.
Smart Grid Applications
Swarm-based demand-response and fault-isolation strategies for resilient distributed energy networks.
Collective Decision-Making
Consensus protocols and stigmergic communication mechanisms enabling robust collective decisions without centralised coordination.
Current Projects
DroneMesh: Multi-UAV Disaster Response Swarm
Multi-UAV swarm coordination system for autonomous disaster search-and-rescue, operating in GPS-denied environments.
GridSwarm: Distributed Energy Network Optimisation
Distributed swarm intelligence for energy grid optimisation — balancing load and reducing outages across decentralised networks.
Related Publications
Interested in Collaborating?
We welcome partnerships with institutions, NGOs, and researchers working at the frontier of AI and this domain.