Dynamic and Self-adaptive Multi-agent Network for Optimal Operation of Engineering Processes

用于工程过程优化运行的动态自适应多智能体网络

• 批准号: RGPIN-2017-04456
• 负责人: DeSilva, Clarence
• 金额: $ 2.26万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=683833
• 关键词: Dynamic; Self; adaptive; Multi; agent

This proposal concerns dynamic and networked engineering processes with sharable resources. Difficult and complex engineering tasks in hazardous and partially-known environments may require cooperative, automated, and wireless operation of autonomous, dynamic, and heterogeneous agents such as robots (mobile or stationary), unmanned aerial vehicles (UAVs), devices that propel in water, and mobile sensor nodes. Multiple sensors, actuators, and other devices may be used, they may be mobile, and may have to be shared among tasks. Examples of engineering applications in this class, which the applicant is involved in are: 1. Spatiotemporal quality assessment (using mobile sensor nodes) of natural sources of water; 2. Multi-robot cooperation for homecare, human rescue, and industrial production; 3. Inspection and repair of pipeline networks that extract and distribute oil bitumen. The main objective of the proposed work is to develop a scalable system framework that will: 1. Accommodate more than one engineering application; 2. Select proper agents for cooperative optimal execution of a specified task, subjected to constraints (e.g., power consumption, system complexity, cost); 3. Adapt the network structure (e.g., add/drop agents; change: sensor location/orientation and activation choice, sampling rate, agent location and pose, connectivity and device parameters) for performance improvement, optimized with respect to multiple objectives. The work involves analytical research, computer simulation, technology development, implementation, and evaluation. The research activities will pertain to adaptive sensing, estimation using sensory data, and multi-sensor data fusion; multi-agent cooperation; and multi-objective and parameter/structure optimization. Specific research outcomes will include new or enhanced: 1. Methodologies for formulating agent models and cost functions (for performance capability, error, etc.), which may employ sensory estimation, device localization and navigation techniques, and self-awareness modeling for intelligent agents; 2. Sensor fusion methodologies, which may incorporate improved and/or hybrid forms of such techniques as the Bayesian approach, Dempster-Shafer evidence theory, nonlinear variations of Kalman filter, and intelligent/soft computing, which have relative advantages and disadvantages; 3. Optimal cooperation and decision making techniques, which may incorporate enhanced or hybridized biology-inspired methods (e.g., swarm intelligence, artificial immune systems, evolutionary computing with mechatronic design quotientMDQ and quality of service as objective functions), Markov decision processMDP, game theory, soft computing, and Pareto-optimal sets. The developed methodologies will be implemented and tested at an industrial site, combining water quality monitoring and pipeline inspection.

该建议涉及具有可共享资源的动态和网络工程流程。在危险和部分知名环境中的困难而复杂的工程任务可能需要自动，动态和异构代理的合作，自动化和无线操作，例如机器人（移动或静止），无人驾驶汽车（无人机）（UAVS），在水和移动传感器Nodes中推动的设备。可以使用多个传感器，执行器和其他设备，它们可能是移动的，并且可能必须在任务之间共享。申请人参与的该类别的工程应用的示例是：1。自然来源的时空质量评估（使用移动传感器节点）； 2。家庭保健，人类救援和工业生产的多机器人合作； 3。检查和修复提取和分配油沥青的管道网络。拟议工作的主要目的是开发一个可扩展的系统框架，该框架将：1。容纳多个工程应用程序； 2。选择适当的代理，以进行合作的最佳执行指定任务，并受到约束（例如，功耗，系统复杂性，成本）； 3。调整网络结构（例如，添加/滴剂代理；更改：传感器位置/方向和激活选择，采样率，代理位置和姿势，连接性和设备参数），以改进性能，以相对于多个目标进行了优化。这项工作涉及分析研究，计算机模拟，技术开发，实施和评估。研究活动将与自适应感测，使用感官数据进行估计以及多传感器数据融合有关；多代理合作；以及多目标和参数/结构优化。具体的研究结果将包括新的或增强的：1。制定代理模型和成本功能的方法（用于性能能力，错误等），这些方法可能采用感官估计，设备定位和导航技术以及对智能代理的自我意识建模； 2。传感器融合方法，可以结合贝叶斯方法，dempster-shafer证据理论，卡尔曼过滤器的非线性变化以及具有相对优势和缺点的智能/软计算等技术的改进和/或杂交形式； 3。最佳合作与决策技术，可能结合了增强或杂交生物学启发的方法（例如，群体智能，人工免疫系统，具有机电剂设计商的进化计算，服务商的进化计算和服务的质量作为目标功能），Markov Decistment ProcessMDP，游戏理论，游戏理论，软计算，软计算，Pareto-pareto-pareto-optimal setsss。开发的方法将在工业场所实施和测试，结合水质监测和管道检查。