Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Foundations of coverage algorithms in autonomic mobile sensor networks

Drones are poised to become a prominent focus of advances in the near future as hardware platforms manufactured via mass production become accessible to consumers in higher quantities at lower costs than ever before. As more ways to utilize such devices become more popular, algorithms for directing the activities of mobile sensors must expand in order to automate their work. This work explores algorithms used to direct the behavior of networks of autonomous mobile sensors, and in particular how such networks can operate to achieve coverage of a field using mobility. We focus special attention to the way limited mobility affects the performance (and other factors) of algorithms traditionally applied to area coverage and event detection problems. Strategies for maximizing event detection and minimizing detection delay as mobile sensors with limited mobility are explored in the first part of this work. Next we examine exploratory coverage, a new way of analyzing sensor coverage, concerned more with covering each part of the coverage field once, while minimizing mobility required to achieve this level of 1-coverage. This analysis is contained in the second part of this work. Extending the analysis of mobility, we next strive to explore the novel topic of disabled mobility in mobile sensors, and how algorithms might react to increase effectiveness given that some sensors have lost mobility while retaining other senses. This work analyzes algorithm effectiveness in light of disabled mobility, demonstrates how this particular failure mode impacts common coverage algorithms, and presents ways to adjust algorithms to mitigate performance losses. --Abstract, page iv

Optimization and Control of Cyber-Physical Vehicle Systems

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined

Communication-aware motion planning in mobile networks

Over the past few years, considerable progress has been made in the area of networked robotic systems and mobile sensor networks. The vision of a mobile sensor network cooperatively learning and adapting in harsh unknown environments to achieve a common goal is closer than ever. In addition to sensing, communication plays a key role in the overall performance of a mobile network, as nodes need to cooperate to achieve their tasks and thus have to communicate vital information in environments that are typically challenging for communication. Therefore, in order to realize the full potentials of such networks, an integrative approach to sensing (information gathering), communication (information exchange), and motion planning is needed, such that each mobile sensor considers the impact of its motion decisions on both sensing and communication, and optimizes its trajectory accordingly. This is the main motivation for this dissertation. This dissertation focuses on communication-aware motion planning of mobile networks in the presence of realistic communication channels that experience path loss, shadowing and multipath fading. This is a challenging multi-disciplinary task. It requires an assessment of wireless link qualities at places that are not yet visited by the mobile sensors as well as a proper co-optimization of sensing, communication and navigation objectives, such that each mobile sensor chooses a trajectory that provides the best balance between its sensing and communication, while satisfying the constraints on its connectivity, motion and energy consumption. While some trajectories allow the mobile sensors to sense efficiently, they may not result in a good communication. On the other hand, trajectories that optimize communication may result in poor sensing. The main contribution of this dissertation is then to address these challenges by proposing a new paradigm for communication-aware motion planning in mobile networks. We consider three examples from networked robotics and mobile sensor network literature: target tracking, surveillance and dynamic coverage. For these examples, we show how probabilistic assessment of the channel can be used to integrate sensing, communication and navigation objectives when planning the motion in order to guarantee satisfactory performance of the network in realistic communication settings. Specifically, we characterize the performance of the proposed framework mathematically and unveil new and considerably more efficient system behaviors. Finally, since multipath fading cannot be assessed, proper strategies are needed to increase the robustness of the network to multipath fading and other modeling/channel assessment errors. We further devise such robustness strategies in the context of our communication-aware surveillance scenario. Overall, our results show the superior performance of the proposed motion planning approaches in realistic fading environments and provide an in-depth understanding of the underlying design trade-off space

Event-based Vision: A Survey

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world

10081 Abstracts Collection -- Cognitive Robotics

From 21.02. to 26.02.2010, the Dagstuhl Seminar 10081 ``Cognitive Robotics \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available