Active Information Gathering Using Distributed Mobile Sensing Networks
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Active Information Gathering Using Distributed Mobile Sensing Networks
An autonomous robot system requires robots to actively gather information using sensors in order to make control decisions. Some problems where autonomous robots are useful include mapping, environmental monitoring, and surveillance. In some cases, information gathering turns into a multiple target tracking (MTT) problem. Usually, an MTT tracker is utilized to recursively estimate both the number of targets and the state of each target. In order to estimate more efficiently and reliably, sensors must balance exploiting current knowledge to track known targets while simultaneously exploring to find information about new targets. This yields to the coverage control problem, which is aimed at maximizing the total sensing capability of a sensing network over the entire mission space. Many applications of sensing networks benefit from utilizing distributed manners, in which cases networks are able to be scaled to large swarms and better tolerate failures of individual sensors. A distributed network requires sensors to exchange data locally and cooperate in decision making globally.This dissertation studies MTT based on random finite set (RFS) for iterative target states estimation and Voronoi-based coverage control algorithms for target tracking. We address a series of four main problems aiming at allowing reliable and efficient target tracking for distributed multi-robot systems in complicated real-world scenarios and push forward the realization of robot coordination techniques. Firstly, we propose novel target estimation and coverage control schemes to incorporate robots with localization uncertainty. Secondly, we improve target search efficiency for teams of robot with no prior knowledge of target models or distributions by enabling active search and environment learning. Thirdly, we allow robots with heterogeneous capacities in perception and kinematics to cooperatively search and track in an efficient way. Lastly, we develop an improved MTT tracker to allow estimating semantic object labels over time. The efficacy of the proposed methods has been validated in series of simulations and/or hardware validations.
Information Networking. Towards Ubiquitous Networking and Services
This volume contains the set of revised selected papers presented at the 21st International Conference on Information Networking (ICOIN 2007), which was held in Estoril, Portugal, January 23–25, 2007. The conference series started under the name of Joint Workshop on Computer Communications, in 1986. At that time, it constituted a technical meeting for researchersand engineers on - ternet technologies in East Asian countries, where several technical networking issues were discussed. In 1993, the meeting was reorganized as an international conference known as ICOIN. Recent conferences were held in Sendai, Japan (2006),Jeju,Korea(2005),Pusan,Korea(2004),Jeju,Korea(2003),Jeju,Korea (2002), Beppu City, Japan (2001), Hsin-chu, Taiwan (2000), and Tokyo, Japan (1999). In 2007, for the ?rst time since its creation, ICOIN took place outside Asia, and we were very pleased to host it in Portugal. ICOIN 2007 was or- nized by INESC-ID and IST/Technical University of Lisbon (Portugal) with the technical co-sponsorship of IEEE Communications Society and IEEE Portugal Section-Computer Society Chapter, in cooperation with the Order of Engineers CollegeofInformaticsEngineering(Portugal),IPSJ(InformationProcessing- ciety of Japan), KISS (Korea Information Science Society), and Lecture Notes in Computer Science (LNCS), Springer, Germany. The papers presented in this volume were selected in two stages: 1) revi- ing and selection for the ICOIN program and 2) on-site presentation review by session chairs or by program committee chairs.
Proceedings of 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control
This book includes original, peer-reviewed research papers from the 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control (CCSICC2021), held in Shenzhen, China on January 19-22, 2022. The topics covered include but are not limited to: reviews and discussions of swarm intelligence, basic theories on swarm intelligence, swarm communication and networking, swarm perception, awareness and location, swarm decision and planning, cooperative control, cooperative guidance, swarm simulation and assessment. The papers showcased here share the latest findings on theories, algorithms and applications in swarm intelligence and cooperative control, making the book a valuable asset for researchers, engineers, and university students alike.