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Verifiable Control Synthesis for Robotic Swarms.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Verifiable Control Synthesis for Robotic Swarms./
作者:
Chen, Ji.
面頁冊數:
1 online resource (135 pages)
附註:
Source: Dissertations Abstracts International, Volume: 83-12, Section: B.
Contained By:
Dissertations Abstracts International83-12B.
標題:
Mechanical engineering. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29168878click for full text (PQDT)
ISBN:
9798819369623
Verifiable Control Synthesis for Robotic Swarms.
Chen, Ji.
Verifiable Control Synthesis for Robotic Swarms.
- 1 online resource (135 pages)
Source: Dissertations Abstracts International, Volume: 83-12, Section: B.
Thesis (Ph.D.)--Cornell University, 2022.
Includes bibliographical references
Swarm robotics is an active research area where large groups of simple robots are developed to perform complex tasks. It has various potential applications such as surveillance, warehouse logistics, and collective construction, because of its large sensing capability, fault tolerance, and collaboration skills that are impossible to a single robot. However, controlling swarm robots to perform high-level tasks automatically and verifiably remains challenging due to the large state space. In this work, I present the verifiable control framework for swarm robots from high-level specifications in different combinations of 4 dimensions: symbolic/continuous levels, centralized/decentralized methods, navigation/formation-based specifications, and non-reactive/reactive tasks.The first contribution of the work is a top-down control framework for non-reactive navigation swarm tasks. At the symbolic level, I propose an integer programming-based method for executing a centralized symbolic plan, and compare it with existing decentralized execution in terms of task efficiency, failure resilience, and computational complexity. At the continuous level, I propose a control barrier function based method which guarantees correct (satisfy all specifications) and safe (no collision) transitions when robots execute the high-level tasks. The trade-offs between centralized and decentralized methods provide guidance to swarm controls to achieve different purposes under different restrictions.The second contribution is a novel abstraction and grammar for location and formation-based swarm specifications. With the proposed abstractions, we developed a centralized control synthesis approach which guarantees that the specified swarm behaviors will be satisfied if feasible. This contribution expands the task space of swarms, and gives insights into controlling a large fleet of autonomous robots to perform complex tasks which require composition of behaviors and coordination of different sub-swarms.The third contribution is an extension to the second, which automatically synthesizes controls for swarms to achieve reactive formation tasks in a decentralized manner. This work utilizes an integer programming-based method to calculate constraints on subswarm sizes given the reactive finite state machine, to ensure a priori feasibility of the task. In addition, a decentralized auction-based algorithm is developed for executing the reactive finite state machine, which satisfies the robot number constraints. Such decentralized frameworks increase the scalability of control synthesis and can be applied to swarm systems with a larger number of robots.The last contribution of this thesis is an automatic approach to redistributing robots according to user requests during the task execution while maintaining the original specifications. The approach includes creating symbolic plans, limiting robot numbers given the constraints, and ensuring all robots to satisfy safety requirements of the given high level tasks. This work further enhance the flexibility and reactivity of swarms performing high-level tasks.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023
Mode of access: World Wide Web
ISBN: 9798819369623Subjects--Topical Terms:
649730
Mechanical engineering.
Subjects--Index Terms:
Formal synthesisIndex Terms--Genre/Form:
542853
Electronic books.
Verifiable Control Synthesis for Robotic Swarms.
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Source: Dissertations Abstracts International, Volume: 83-12, Section: B.
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Advisor: Kress Gazit, Hadas.
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Thesis (Ph.D.)--Cornell University, 2022.
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Includes bibliographical references
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Swarm robotics is an active research area where large groups of simple robots are developed to perform complex tasks. It has various potential applications such as surveillance, warehouse logistics, and collective construction, because of its large sensing capability, fault tolerance, and collaboration skills that are impossible to a single robot. However, controlling swarm robots to perform high-level tasks automatically and verifiably remains challenging due to the large state space. In this work, I present the verifiable control framework for swarm robots from high-level specifications in different combinations of 4 dimensions: symbolic/continuous levels, centralized/decentralized methods, navigation/formation-based specifications, and non-reactive/reactive tasks.The first contribution of the work is a top-down control framework for non-reactive navigation swarm tasks. At the symbolic level, I propose an integer programming-based method for executing a centralized symbolic plan, and compare it with existing decentralized execution in terms of task efficiency, failure resilience, and computational complexity. At the continuous level, I propose a control barrier function based method which guarantees correct (satisfy all specifications) and safe (no collision) transitions when robots execute the high-level tasks. The trade-offs between centralized and decentralized methods provide guidance to swarm controls to achieve different purposes under different restrictions.The second contribution is a novel abstraction and grammar for location and formation-based swarm specifications. With the proposed abstractions, we developed a centralized control synthesis approach which guarantees that the specified swarm behaviors will be satisfied if feasible. This contribution expands the task space of swarms, and gives insights into controlling a large fleet of autonomous robots to perform complex tasks which require composition of behaviors and coordination of different sub-swarms.The third contribution is an extension to the second, which automatically synthesizes controls for swarms to achieve reactive formation tasks in a decentralized manner. This work utilizes an integer programming-based method to calculate constraints on subswarm sizes given the reactive finite state machine, to ensure a priori feasibility of the task. In addition, a decentralized auction-based algorithm is developed for executing the reactive finite state machine, which satisfies the robot number constraints. Such decentralized frameworks increase the scalability of control synthesis and can be applied to swarm systems with a larger number of robots.The last contribution of this thesis is an automatic approach to redistributing robots according to user requests during the task execution while maintaining the original specifications. The approach includes creating symbolic plans, limiting robot numbers given the constraints, and ensuring all robots to satisfy safety requirements of the given high level tasks. This work further enhance the flexibility and reactivity of swarms performing high-level tasks.
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