Overview
Project Overview:
Designed and implemented an intelligent coverage path planning framework for multi-agent systems operating in environments with different characteristics. A hybrid approach combining Ant Colony Optimization (ACO) and Genetic Algorithm (GA) improved convergence speed and ensured efficient task distribution.
Key Outcomes:
• Increased mission coverage efficiency
• Reduced operation time in dynamic environments
Core Skills: Swarm intelligence, metaheuristic optimization, simulation modeling
Application Domains: Industrial inspection, agriculture automation, surveillance robotics
