This research dissertation addresses the significant challenge of Multi-Robot Multi-Target Tracking (MR-MTT), a critical system in various scenarios, including search-and-rescue missions, surveillance, and environmental monitoring. MR-MTT involves coordinating a team of robots to track multiple dynamic targets in diverse environments. This challenge requires efficient coordination among the robots to ensure effective tracking of all targets. The core of this challenge lies in developing efficient strategies for estimation, communication, and control within these robotic systems. Our goal is to create and test different solutions to this general problem.
A significant focus of this research is on the estimation aspect of MR-MTT. The system employs a novel distributed Multiple Hypothesis Tracker (MHT) for accurate estimation of both the number and states of multiple targets. A standout feature of our methodology is the introduction of an innovative data association method, designed to reallocate target tracks among the robots, thereby enhancing the collective tracking accuracy and efficiency of the team. This approach is particularly beneficial in scenarios with numerous targets and highly dynamic movements, as it allows for more flexible and responsive tracking.
In addition to estimation, a substantial portion of this research focuses on the development of advanced control strategies to enhance the team's efficiency in locating all targets and achieving this goal more swiftly. We have integrated Particle Swarm Optimization (PSO), Simulated Annealing (SA), Ant Colony Optimization (ACO) and Artificial Immune System (AIS)into the MR-MTT systems with an estimation method using the PHD filter. This integration aims to optimize the robots' trajectories and search patterns, leveraging the strengths of these metaheuristic-based algorithms to strike a balance between exploration and exploitation. Such optimization is crucial for enhancing the overall efficiency and effectiveness of MR-MTT systems.
Furthermore, this dissertation includes a comprehensive system-level analysis and prediction component through dimensionless variable analysis. We have developed an analytical framework to evaluate and predict the performance of MR-MTT systems under various operational scenarios and environmental conditions. This framework is intended to provide deep insights into the critical performance determinants and their interrelations, guiding the design and optimization of MR-MTT systems. The anticipated outcomes of this research include improved accuracy in target tracking, enhanced performance metrics for MR-MTT systems, and valuable insights for the future design and management of sophisticated multi-robot systems.
The expected outcomes of this research are multifold: enhanced accuracy in target tracking, improved performance metrics for MR-MTT systems, and valuable insights for the future development and management of complex multi-robot systems. Through this proposal, we aim to contribute significantly to the field of robotic coordination and tracking, addressing critical needs in various high-impact applications. / Mechanical Engineering
| Identifer | oai:union.ndltd.org:TEMPLE/oai:scholarshare.temple.edu:20.500.12613/10260 |
| Date | 05 1900 |
| Creators | Xin, Pujie |
| Contributors | Dames, Philip, Soudbakhsh, Damoon, Chen, Yuzhou, Ashrafiuon, Hashem |
| Publisher | Temple University. Libraries |
| Source Sets | Temple University |
| Language | English |
| Detected Language | English |
| Type | Thesis/Dissertation, Text |
| Format | 125 pages |
| Rights | IN COPYRIGHT- This Rights Statement can be used for an Item that is in copyright. Using this statement implies that the organization making this Item available has determined that the Item is in copyright and either is the rights-holder, has obtained permission from the rights-holder(s) to make their Work(s) available, or makes the Item available under an exception or limitation to copyright (including Fair Use) that entitles it to make the Item available., http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | http://dx.doi.org/10.34944/dspace/10222, Theses and Dissertations |
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