Optimal Strategies for Cooperative Autonomous Systems - 20-000000768
Abstract
We propose to develop, implement, and test motion planning algorithms for cooperative multivehicle systems. In this work, a cooperative multi-vehicle system refers to a group of heterogeneous (ground, aerial, marine) vehicles able to autonomously navigate an unknown environment while achieving cooperative tasks safely and effectively. Examples of cooperative tasks include swarming, complete area coverage, coordination, cooperative mapping andlocalization, formation. The algorithms needed to achieve these tasks have broad applicability in several domains, including search and rescue, patrolling, surveillance, and mine-counter missions, to mention but a few. The project will develop novel algorithms for optimal motion planning, which will be supplemented by rigorous theoretical and quantitative analysis on the effectiveness and safety of the proposed solution. The performance of the algorithms will be evaluated and tuned in an indoor lab setting at the CAS Lab, at the University of Iowa.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 06, 2021
- Source ID
- N000142112091
Entities
People
- Venanzio Cichella
Organizations
- Office of Naval Research
- United States Navy
- University of Iowa