关于此电子书
Search and Classification Using Multiple Autonomous Vehicles provides a comprehensive study of decision-making strategies for domain search and object classification using multiple autonomous vehicles (MAV) under both deterministic and probabilistic frameworks. It serves as a first discussion of the problem of effective resource allocation using MAV with sensing limitations, i.e., for search and classification missions over large-scale domains, or when there are far more objects to be found and classified than there are autonomous vehicles available. Under such scenarios, search and classification compete for limited sensing resources. This is because search requires vehicle mobility while classification restricts the vehicles to the vicinity of any objects found. The authors develop decision-making strategies to choose between these competing tasks and vehicle-motion-control laws to achieve the proposed management scheme. Deterministic Lyapunov-based, probabilistic Bayesian-based, and risk-based decision-making strategies and sensor-management schemes are created in sequence. Modeling and analysis include rigorous mathematical proofs of the proposed theorems and the practical consideration of limited sensing resources and observation costs. A survey of the well-developed coverage control problem is also provided as a foundation of search algorithms within the overall decision-making strategies. Applications in both underwater sampling and space-situational awareness are investigated in detail. The control strategies proposed in each chapter are followed by illustrative simulation results and analysis.
Academic researchers and graduate students from aerospace, robotics, mechanical or electrical engineering backgrounds interested in multi-agent coordination and control, in detection and estimation or in Bayes filtration will find this text of interest.
Academic researchers and graduate students from aerospace, robotics, mechanical or electrical engineering backgrounds interested in multi-agent coordination and control, in detection and estimation or in Bayes filtration will find this text of interest.
作者简介
Yue Wang's research areas include decision-making and sensor management for search, classification and tracking using multiple autonomous vehicles, distributed estimation and control of networked cyber-physical systems, and dynamic coverage control over large-scale domains. She got her Ph.D. degree in Mechanical Engineering at Worcester Polytechnic Institute in May 2011. She is currently a postdoctoral research associate in the Electrical Engineering Department at University of Notre Dame and will be an Assistant Professor in the Mechanical Engineering Department in Clemson University from 2012.
Islam I. Hussein's research areas include nonlinear and evolutionary dynamics, control and optimization, detection and estimation, risk-based decision-making, sensor/communication networks, and agent-based systems. He is an assistant professor in the Mechanical Engineering Department at Worcester Polytechnic Institute. From 2005 to 2006, he held a postdoctoral research associate position at the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. He was awarded the Ph.D. degree in Aerospace Engineering in 2005 and the M.Sc. degrees in Aerospace Engineering and Applied Mathematics in 2002 from the University of Michigan.
Islam I. Hussein's research areas include nonlinear and evolutionary dynamics, control and optimization, detection and estimation, risk-based decision-making, sensor/communication networks, and agent-based systems. He is an assistant professor in the Mechanical Engineering Department at Worcester Polytechnic Institute. From 2005 to 2006, he held a postdoctoral research associate position at the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. He was awarded the Ph.D. degree in Aerospace Engineering in 2005 and the M.Sc. degrees in Aerospace Engineering and Applied Mathematics in 2002 from the University of Michigan.
为此电子书评分
欢迎向我们提供反馈意见。
如何阅读
智能手机和平板电脑
笔记本电脑和台式机
您可以使用计算机的网络浏览器聆听您在 Google Play 购买的有声读物。
电子阅读器和其他设备
如果要在 Kobo 电子阅读器等电子墨水屏设备上阅读，您需要下载一个文件，并将其传输到相应设备上。若要将文件传输到受支持的电子阅读器上，请按帮助中心内的详细说明操作。
