Technical point of contact: Behzad Kamgar-Parsi, Office of Naval Research
Period of activity: 2018-2022
Collaborators: Lu Feng (PI, Univ of Virginia), Zsolt Kira (Georgia Tech), Pratap Tokekar (Univ of Maryland)
Overview of the Project
|The objective of this project is to develop theory and algorithms for decentralized perception and temporal logic planning for a team of autonomous agents collaboratively operating in dynamic, uncertain and unstructured environments where large volumes of heterogeneous streaming data are collected.
A key challenge is how to derive intelligence from the massive, distributed, and diverse data sources, and enable the rapid decision-making of autonomous agents. We propose a unified theoretical framework of decentralized perception and planning to address these two needs. The project has three research thrusts that are tightly integrated into a rigorous closed-loop framework.
- Thrust I – Decentralized perception for planning: How to integrate information from multiple sensing modalities and diverse sources, filter out irrelevant information, and learn distributed and shared representations of the environment in a team of agents?
- Thrust II – Collaborative decentralized temporal logic planning: How to make planning decisions for the distributed team of autonomous agents based on the semantic world model with uncertainty learned in Thrust I, subject to a rich set of temporal logic specifications representing mission goals and problem constraints?
- Thrust III – Using planning and communication to guide perception: How to close the loop by using information from planning and communication to guide and achieve task-aware, active perception?