The goal of multi-agent control for robots is to develop theoretical foundations that enable autonomous systems to operate effectively. This approach demonstrates how collaboration among multiple agents can enhance the overall capabilities of each individual member, leading to improved performance and functionality in complex tasks.
Ongoing Project
- Detection and Surveillance of Harmful Algal Blooms by Integrating Satellite Monitoring with In-situ Adaptive Sampling
- Harmful algal blooms (HABs) pose a significant threat to public health, through their production of toxins, seafood contamination, and ecosystem disruption. Presently, HAB monitoring programs rely on limited measurements from fixed site monitoring or periodic shipboard surveys. These approaches often underestimate HAB occurrences, either due to measurements being taken outside the bloom’s actual boundaries, surveys conducted before or after the bloom’s peak, or lack of personnel to respond rapidly to HAB reports. Consequently, HABs could be developing unnoticed, leaving communities without timely warnings or awareness of the potential impacts on recreational activities and subsistence fishing. Our goal is to develop and validate an innovative methodology for swiftly mapping and issuing warnings about HABs occurring in the Lafayette and York Rivers and issuing warnings/notifications to local communities. This methodology has the potential to be highly automated using ROVs and surface vehicle.
- Funded by Multidisciplinary Coastal Adaptation & Resilience (ICAR) Research Seed Funding
Past Project
- Distributed Control and Estimation for Scattering Layer by Multiple Autonomous Underwater Vehicles (Postdoc, 2021-2023)
- Funded by Northrop Grumman-UMD seed grant & Army Research Laboratory (ARL)
- Synchronous rendezvous in geophysical flows (PhD,2016-2019)
- Funded by Office of Naval Research (ONR)