Modeling and Simulation of Multiple Agents in a Dynamic Environment

Autonomous systems operating in remote and harsh environments must maintain reliable perception despite changing environmental conditions, sensor degradation, and limited computational resources. The effectiveness of a sensing modality can vary throughout a mission, making static sensor configurations inefficient and potentially unreliable. This project explores adaptive sensor selection as a mechanism for improving perception resilience and computational efficiency in long-duration autonomous missions.

Interns: Minjia Huang, Pearl Kamalu

Mentor: Anthony Thompson (REDD/RQB)