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Unit 1: Swarm Intelligence Foundations
Biological inspiration (ants, bees, birds, fish schooling), Boids model (separation, alignment, cohesion), Reynolds rules and flocking behavior, Particle Swarm Optimization (PSO: velocity update, inertia weight), Ant Colony Optimization (ACO: pheromone trails, evaporation), Artificial Bee Colony (ABC), Swarm stability analysis.
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Unit 2: Multi-Robot Communication and Coordination
Communication topologies (centralized, decentralized, hybrid), Consensus algorithms (average, leader election), Task allocation (CBBA, auction-based), Formation control (virtual structures, leader-follower), Potential field methods (artificial potentials, collision avoidance), Graph-theoretic approaches (Riemannian manifolds).
03
Unit 3: Swarm Robotics Algorithms
Coverage control (Voronoi partitions, Lloyd algorithm), Foraging and patrolling strategies, Flocking with obstacles, Self-assembly and shape formation, Density control and deployment, Scalable coordination (local interactions, emergent behavior), Scalability analysis (communication overhead, convergence time).
04
Unit 4: Distributed Estimation and Mapping
Multi-robot SLAM (centralized, decentralized, DDF-SLAM), Data association (JPDDA, Murty's algorithm), Cooperative localization (EKF/UKF fusion), Relative pose estimation (anchor nodes), Graph SLAM optimization (pose graph, factor graphs), Outlier rejection and robust estimation.
05
Unit 5: Advanced Topics and Applications
Heterogeneity in swarms (specialized roles), Fault tolerance and resilience, Learning in multi-agent systems (MARL, QMIX), Swarm reinforcement learning, Real-world applications (search-rescue, agriculture, warehouse automation), Hardware platforms (Khepera, Kilobot, TurtleBot swarm), Standardization (ROS2 multi-robot, MQTT/IoT protocols).