Novel Algorithms for Multi-Agent Autonomous Telerobotic Surveillance and Reconnaissance System

Project starts in 2020.

The advent of network-based telerobotic cameras, installed on aerial vehicles or mini unmanned ground vehicles enable multiple autonomous agents in the battlefield to interact with a remote physical environment using shared resources. It provides large streams of information to decision makers to conduct military operations such as intelligence, surveillance and reconnaissance, in harsh and hostile environment where it is tedious for humans to collect information. However, the telerobotic cameras system requires huge amount of data processing and storage units because of redundant (or overlapping) and unimportant information (videos or images) provided by the cameras.

The objective of this project is to develop novel algorithms for the multi-agent autonomous telerobotic surveillance and reconnaissance system by solving a set of stochastic combinatorial optimization problems. More specifically, our goals are as follows: (a) To efficiently manage this information using limited resources such that a subset of the information with maximum priority is captured; and (b) To utilize this information for identifying vulnerabilities in the logistics network, whose disruption will impose a substantial damage to the rescue missions, against enemy’s unforeseen attacks using knowledge of the enemy’s capabilities.

Publications:

• S. Kang, M. Bansal, “Distributionally risk-averse and risk-receptive network interdiction problems,” Networks 81(1), 3-22, 2022. https://doi.org/10.1002/net.22114
  Code/Instances will be available at https://github.com/Bansal-ORGroup/NetworkInterdiction
• K. Kulkarni, M. Bansal, “Discrete Multi-Module Capacitated Lot-Sizing Problems with Multiple Items,” Operations Research Letters 50 (2), 168-175, 2022. https://doi.org/10.1016/j.orl.2022.01.002
  Code and Instances will be made available at https://github.com/Bansal-ORGroup/Multi-Item-Discrete-MCLS
• S. Park and M. Bansal, “Algorithms for Cameras View-Frame Placement Problems in the Presence of an Adversary and Distributional Ambiguity,” IEEE Transactions on Automation Science and Engineering (under review), 2023.
  Code and Instances will be made available at this website: https://github.com/Bansal-ORGroup/AdversarialCameraViewFramePlacement
• M. Bansal and P. Shojaee, Planar maximum coverage location problem with partial coverage, continuous demand, and adjustable quality of service,” Technical Report, 2021. http://arxiv.org/abs/2012.​09063
  Code and Instances will be available at https://github.com/Bansal-ORGroup/PMCLP-PCR-QoS

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