Multi-Agent Coverage Path Planning - Wildlife Monitoring and Beyond
Explore multi-agent coverage path planning for wildlife monitoring and beyond in this research seminar from Stanford University. Delve into the challenges of autonomous aerial surveys, focusing on applications like monitoring Adelie penguin colonies in Antarctica. Learn about novel algorithms using satisfiability modulo theory (SMT) to solve complex path planning problems with multiple agents and real-world constraints. Discover how these techniques can be applied to wildlife conservation, field operations, and other disciplines requiring efficient area coverage. Gain insights into the practical implementation of autonomous survey planning, including considerations for take-off and landing locations, battery life, and legal restrictions. Follow the journey from theoretical development to field testing in harsh Antarctic conditions, and explore future directions for optimizing survey fleets, adapting to changing environments, and expanding applications beyond wildlife monitoring.