CRII: RI: Distributed, Stable and Robust Topology Control: New Methods for Asymmetrically Interacting Multi-Robot Teams
CRII:RI:分布式、稳定和鲁棒的拓扑控制:非对称交互多机器人团队的新方法
基本信息
- 批准号:1657235
- 负责人:
- 金额:$ 17.43万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-04-01 至 2019-03-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Recent years have seen a rapid increase of autonomous robotics in critical segments of research and industry. However, autonomy in teams of robots remains somewhat in its infancy. This project therefore aims to eliminate three assumptions that currently limit the autonomous control of multi-robot teams: (1) that complete system information is available to all robots at all times; (2) that robot-to-robot interactions are symmetric among team members (i.e., I see you and you see me); and (3) that interactions among robots provide enough information to guarantee predictable and safe robot motion. This project will tackle such restrictions by developing new methods for explicitly controlling robot-to-robot interaction when the above assumptions are absent, with validation in field experiments using commercial off-the-shelf robotic and Internet of Things (IoT) sensor platforms. The project outcomes will find broad relevance in applications spanning intelligent transportation, precision agriculture, autonomous construction, and defense, while allowing for deeper experimentation outside of laboratories. Finally, the project includes a comprehensive outreach plan consisting of: (1) K-12 academic experiences for underrepresented students; (2) graduate curriculum; and (3) open-source contributions to the robotics community.Towards the above goals, this project will intersect novel techniques from control and graph theory to derive stability guarantees for a new class of asymmetric topology control laws. The theoretical approaches will enable guaranteed coordination for a large class of distributed multi-robot systems. Specifically, this project will focus on the following objectives of developing: (1) nonlinear motion controllers that guarantee stable multi-robot coordination for an identified class of asymmetric robot interactions; (2) distributed algorithms for determining stable transitions in asymmetric communication and sensing topologies; (3) extensions for hardware safe control inputs and robustness to external disturbance; and (4) field experiments with aerial and ground robots, and an IoT sensor network in a target tracking regime.
近年来,在研究和行业的关键细分市场中,自动机器人技术迅速增加。 但是,机器人团队的自主权仍处于起步阶段。 因此,该项目旨在消除当前限制多机器人团队自主控制的三个假设:(1)所有机器人都可以使用完整的系统信息; (2)机器人到机器人的互动是团队成员中对称的(即,我见到你,你看到我); (3)机器人之间的相互作用提供了足够的信息来保证可预测且安全的机器人运动。 当缺乏上述假设时,该项目将通过开发新的方法来应对机器人到机器人的互动,从而解决此类限制,并在现场实验中使用商业现成的机器人和互联网(IoT)传感器平台进行验证。 该项目的结果将在跨越智能运输,精密农业,自动建筑和防御的应用中找到广泛的相关性,同时允许在实验室之外进行更深入的实验。 最后,该项目包括一项全面的外展计划,其中包括:(1)针对代表性不足的学生的K-12学术经验; (2)研究生课程; (3)对机器人社区的开源贡献。要提出上述目标,该项目将与新的技术从控制和图理论相交,以获得新的不对称拓扑控制法的稳定性保证。 理论方法将为大量的分布式多机器人系统提供保证的协调。 具体而言,该项目将集中于以下开发目标:(1)为确定的一系列不对称机器人相互作用提供稳定的多机器人协调的非线性运动控制器; (2)分布式算法,用于确定不对称通信和传感拓扑中稳定过渡的分布算法; (3)硬件安全控制输入的扩展和外部干扰的鲁棒性; (4)具有空中和地面机器人的现场实验,以及目标跟踪方案中的IoT传感器网络。
项目成果
期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Stable motion and distributed topology control for multi-agent systems with directed interactions
- DOI:10.1109/cdc.2017.8264165
- 发表时间:2017-12
- 期刊:
- 影响因子:0
- 作者:Pratik Mukherjee;A. Gasparri;Ryan K. Williams
- 通讯作者:Pratik Mukherjee;A. Gasparri;Ryan K. Williams
Distributed Connectivity Maintenance in Multi-Agent Systems with Field of View Interactions
- DOI:10.23919/acc.2019.8814457
- 发表时间:2019-07
- 期刊:
- 影响因子:0
- 作者:Matteo Santilli;Pratik Mukherjee;A. Gasparri;Ryan K. Williams
- 通讯作者:Matteo Santilli;Pratik Mukherjee;A. Gasparri;Ryan K. Williams
Experimental Validation of Stable Coordination for Multi-Robot Systems with Limited Fields of View using a Portable Multi-Robot Testbed
使用便携式多机器人测试台对有限视场多机器人系统的稳定协调进行实验验证
- DOI:
- 发表时间:2019
- 期刊:
- 影响因子:0
- 作者:Mukherjee, P.;Santilli, M.;Gasparri, A.;Williams, R.
- 通讯作者:Williams, R.
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Ryan Williams其他文献
Sharp threshold results for computational complexity
计算复杂度的尖锐阈值结果
- DOI:10.1145/3357713.338428310.1145/3357713.3384283
- 发表时间:20202020
- 期刊:
- 影响因子:0
- 作者:Lijie Chen;Ce Jin;Ryan WilliamsLijie Chen;Ce Jin;Ryan Williams
- 通讯作者:Ryan WilliamsRyan Williams
Natural proofs versus derandomization
自然证明与去随机化
- DOI:10.1145/2488608.248861210.1145/2488608.2488612
- 发表时间:20122012
- 期刊:
- 影响因子:0
- 作者:Ryan WilliamsRyan Williams
- 通讯作者:Ryan WilliamsRyan Williams
Promoting Knowledge Accumulation About Intervention Effects: Exploring Strategies for Standardizing Statistical Approaches and Effect Size Reporting
促进干预效果知识积累:探索标准化统计方法和效应量报告的策略
- DOI:10.3102/0013189x21105131910.3102/0013189x211051319
- 发表时间:20212021
- 期刊:
- 影响因子:8.2
- 作者:Joseph A. Taylor;T. Pigott;Ryan WilliamsJoseph A. Taylor;T. Pigott;Ryan Williams
- 通讯作者:Ryan WilliamsRyan Williams
Utility of in-session assessments during cognitive behavioral therapy for depression after traumatic brain injury: Results from a randomized controlled trial.
创伤性脑损伤后抑郁症认知行为治疗期间评估的效用:随机对照试验的结果。
- DOI:10.3233/nre-23021810.3233/nre-230218
- 发表时间:20242024
- 期刊:
- 影响因子:2
- 作者:Jennifer M. Erickson;Ryan Williams;C. Bombardier;J. FannJennifer M. Erickson;Ryan Williams;C. Bombardier;J. Fann
- 通讯作者:J. FannJ. Fann
Inductive Time-Space Lower Bounds for Sat and Related Problems
Sat 及相关问题的归纳时空下界
- DOI:10.1007/s00037-007-0221-110.1007/s00037-007-0221-1
- 发表时间:20062006
- 期刊:
- 影响因子:1.4
- 作者:Ryan WilliamsRyan Williams
- 通讯作者:Ryan WilliamsRyan Williams
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Ryan Williams的其他基金
Examining relationships among teacher professional learning and associated teacher and student outcomes in math and science: A meta-analytic approach to mediation and moderation
检查教师专业学习与数学和科学方面相关教师和学生成果之间的关系:调解和调节的元分析方法
- 批准号:23005442300544
- 财政年份:2023
- 资助金额:$ 17.43万$ 17.43万
- 项目类别:Continuing GrantContinuing Grant
CAREER: Robots that Plan Interactions, Come and Go, and Build Trust
职业:规划交互、来来去去并建立信任的机器人
- 批准号:20467702046770
- 财政年份:2021
- 资助金额:$ 17.43万$ 17.43万
- 项目类别:Continuing GrantContinuing Grant
AF: Small: Lower Bounds in Complexity Theory Via Algorithms
AF:小:通过算法实现复杂性理论的下界
- 批准号:21275972127597
- 财政年份:2021
- 资助金额:$ 17.43万$ 17.43万
- 项目类别:Standard GrantStandard Grant
CPS: Medium: Computation-Aware Autonomy for Timely and Resilient Multi-Agent Systems
CPS:中:及时且有弹性的多代理系统的计算感知自治
- 批准号:19320741932074
- 财政年份:2019
- 资助金额:$ 17.43万$ 17.43万
- 项目类别:Standard GrantStandard Grant
NRI: INT: Balancing Collaboration and Autonomy for Multi-Robot Multi-Human Search and Rescue
NRI:INT:平衡多机器人多人搜索和救援的协作与自主
- 批准号:18304141830414
- 财政年份:2018
- 资助金额:$ 17.43万$ 17.43万
- 项目类别:Standard GrantStandard Grant
CAREER: Common Links in Algorithms and Complexity
职业:算法和复杂性的常见联系
- 批准号:17416151741615
- 财政年份:2017
- 资助金额:$ 17.43万$ 17.43万
- 项目类别:Continuing GrantContinuing Grant
AF:Small:Limitations on Algebraic Methods via Boolean Complexity Theory
AF:Small:布尔复杂性理论对代数方法的限制
- 批准号:17416381741638
- 财政年份:2017
- 资助金额:$ 17.43万$ 17.43万
- 项目类别:Standard GrantStandard Grant
AF:Small:Limitations on Algebraic Methods via Boolean Complexity Theory
AF:Small:布尔复杂性理论对代数方法的限制
- 批准号:16175801617580
- 财政年份:2016
- 资助金额:$ 17.43万$ 17.43万
- 项目类别:Standard GrantStandard Grant
NRI: Coordinated Detection and Tracking of Hazardous Agents with Aerial and Aquatic Robots to Inform Emergency Responders
NRI:与空中和水上机器人协调检测和跟踪危险物质,以通知紧急救援人员
- 批准号:16379151637915
- 财政年份:2016
- 资助金额:$ 17.43万$ 17.43万
- 项目类别:Standard GrantStandard Grant
CAREER: Common Links in Algorithms and Complexity
职业:算法和复杂性的常见联系
- 批准号:15526511552651
- 财政年份:2015
- 资助金额:$ 17.43万$ 17.43万
- 项目类别:Continuing GrantContinuing Grant
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