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Perimeter Defense With Multi-Robot Systems Austin Ku Chen

Dissertations & Theses @ University of Pennsylvania Available online

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Format:
Book
Thesis/Dissertation
Author/Creator:
Chen, Austin Ku, author.
Contributor:
University of Pennsylvania. Computer and Information Science., degree granting institution.
Language:
English
Subjects (All):
Robotics.
Computer science.
Electrical engineering.
0771.
0984.
0544.
Local Subjects:
Robotics.
Computer science.
Electrical engineering.
0771.
0984.
0544.
Physical Description:
1 electronic resource (153 pages)
Contained In:
Dissertations Abstracts International 86-07B
Place of Publication:
Ann Arbor : ProQuest Dissertations and Theses, 2024
Language Note:
English
Summary:
Perimeter defense is a key challenge in many real-world scenarios such as airport security, convoy protection, and self-driving cars. To successfully achieve perimeter defense, a defender must solve several fundamental problems such as target tracking, resource allocation, and pursuit evasion. It is also crucial to consider the capabilities of defenders when creating perimeter defense strategies; a control policy intended for fast agents may perform poorly when used with slow agents. Existing literature has divided a defender's overall fitness into physical capability, which determines how well it may deter intruders, and informational capability, which encompasses knowledge of the intruder's location and actions. Perimeter defense strategies have been investigated across a broad range of physical and informational capabilities and can change substantially based upon the team's relative strengths. This dissertation expands the perimeter defense field by considering previously unexplored regions of defender team capability. In contrast to previous works which only explore scenarios with limited information, we investigate a defender that must contend with adversarially manipulated information. The adversary in this situation leverages its informational advantage to deceive the defender and achieve higher task performance. In addition, we consider a new axis of multi-robot capability which describes the team sizes of both the defender and intruder. This direction is especially important to consider given the recent advances in multi-robot systems. We present control policies across a range of physical and informational capabilities with the added assumption of arbitrarily large teams. These approaches are computationally efficient and demonstrate an improvement in empirical performance over few-agent extensions from previous works. The presented contributions show the importance of using the correct perimeter defense algorithm as a function of each team's physical, (possibly deceptive) informational, and multi-robot capabilities
Notes:
Source: Dissertations Abstracts International, Volume: 86-07, Section: B.
Advisors: Kumar, Vijay; Pappas, George J. Committee members: Eaton, Eric; Hsieh, M. Ani; Ribeiro, Alejandro; Shishika, Daigo
Ph.D. University of Pennsylvania 2024
Local Notes:
School code: 0175
ISBN:
9798302183149
Access Restriction:
Restricted for use by site license

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