Cooperative Localization for Teams of Low Size, Weight, and Power (SWAP) Autonomous Assets
Abstract
Demands on autonomous systems are increasing over time. For example, a team of autonomous drones may be required to collaborate in order to enter and safely navigate unknown environments, even when communication among them is impaired. Simultaneously, many autonomous systems must operate with low size, weight, and power (SWAP). For example, small, lightweight drones may only carry small batteries and low-power computers onboard. What results is an increase in demands for reliable autonomous performance alongside decreasing resources to perform. While the research community has begun to grapple with these problems, there remains a pressing need for new foundations for autonomy that are designed with low-SWAP autonomous assets in mind. To help address this need, this project will develop fundamentally novel techniques for the task of cooperative localization in teams of low-SWAP assets. We focus on localizationbecause it is often a requirement for many tasks in disaggregated autonomy.For example, a collection of assets conducting a search and rescue mission must first localize within their search area to understand where they are located within it before their search can begin. In fact, localization is required by many other classes of autonomy tasks, such as intelligence, surveillance, and reconnaissance (ISR) tasks and sweeping an area for hazards. In such cases, the ability to localize is essential, and the developments of this project will help close a critical gap between theory and practice by providing localization capabilities to the broad spectrum of other behaviors that need them. This project will focus in particular on providing guarantees on the quality of localization attained by disaggregated autonomous systems with low size, weight, and power. We will approach this along two complementary lines of inquiry: (i) How should localization problems be encoded for low-SWAP assets? The choice of mathematical formulation has a substantialimpact on the computations and communications that are required of assets. For low-SWAP assets, we propose the use of dual quaternions because they offer a unified representation of assets locations and headings, which can significantly lower the number of sensor readings, computations, and communications required to localize. (ii) How do the capabilities of low-SWAP assets affect their performance? We will develop performance guarantees that are ``bottom-up in the sense that we will account for the contribution of each individual sensor reading, computation, and communication to the accuracy of assets localization. From that characterization, we will be able to determine exactly what operations assets must execute in order to attain a desired level of performance. Approved for Public Release.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 15, 2024
- Source ID
- N000142412331
Entities
People
- Matthew Hale
Organizations
- Georgia Tech Research Corporation
- Office of Naval Research
- United States Navy