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

Robust Localization and Efficient Path Planning for Mobile Sensor Networks

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 2. 오성회.The area of wireless sensor networks has flourished over the past decade due to advances in micro-electro-mechanical sensors, low power communication and computing protocols, and embedded microprocessors. Recently, there has been a growing interest in mobile sensor networks, along with the development of robotics, and mobile sensor networks have enabled networked sensing system to solve the challenging issues of wireless sensor networks by adding mobility into many different applications of wireless sensor networks. Nonetheless, there are many challenges to be addressed in mobile sensor networks. Among these, the estimation for the exact location is perhaps the most important to obtain high fidelity of the sensory information. Moreover, planning should be required to send the mobile sensors to sensing location considering the region of interest, prior to sensor placements. These are the fundamental problems in realizing mobile sensor networks which is capable of performing monitoring mission in unstructured and dynamic environment. In this dissertation, we take an advantage of mobility which mobile sensor networks possess and develop localization and path planning algorithms suitable for mobile sensor networks. We also design coverage control strategy using resource-constrained mobile sensors by taking advantages of the proposed path planning method. The dissertation starts with the localization problem, one of the fundamental issue in mobile sensor networks. Although global positioning system (GPS) can perform relatively accurate localization, it is not feasible in many situations, especially indoor environment and costs a tremendous amount in deploying all robots equipped with GPS sensors. Thus we develop the indoor localization system suitable for mobile sensor networks using inexpensive robot platform. We focus on the technique that relies primarily on the camera sensor. Since it costs less than other sensors, all mobile robots can be easily equipped with cameras. In this dissertation, we demonstrate that the proposed method is suitable for mobile sensor networks requiring an inexpensive off-the-shelf robotic platform, by showing that it provides consistently robust location information for low-cost noisy sensors. We also focus on another fundamental issue of mobile sensor networks which is a path planning problem in order to deploy mobile sensors in specific locations. Unlike the traditional planning methods, we present an efficient cost-aware planning method suitable for mobile sensor networks by considering the given environment, where it has environmental parameters such as temperature, humidity, chemical concentration, stealthiness and elevation. A global stochastic optimization method is used to improve the efficiency of the sampling based planning algorithm. This dissertation presents the first approach of sampling based planning using global tree extension. Based on the proposed planning method, we also presents a general framework for modeling a coverage control system consisting of multiple robots with resource constraints suitable for mobile sensor networks. We describe the optimal informative planning methods which deal with maximization problem with constraints using global stochastic optimization method. In addition, we describe how to find trajectories for multiple robots efficiently to estimate the environmental field using information obtained from all robots.Chapter 1 Introduction 1 1.1 Mobile Sensor networks 1 1.1.1 Challenges 3 1.2 Overview of the Dissertation 4 Chapter 2 Background 7 2.1 Localization in MSNs 7 2.2 Path planning in MSNs 10 2.3 Informative path planning in MSNs 12 Chapter 3 Robust Indoor Localization 15 3.1 An Overview of Coordinated Multi-Robot Localization 16 3.2 Multi-Robot Localization using Multi-View Geometry 19 3.2.1 Planar Homography for Robot Localization 20 3.2.2 Image Based Robot Control 21 3.3 Multi-Robot Navigation System 25 3.3.1 Multi-Robot System 26 3.3.2 Multi-Robot Navigation 30 3.4 Experimental Results 32 3.4.1 Coordinated Multi-Robot Localization: Single-Step 32 3.4.2 Coordinated Multi-Robot Localization: Multi-Step 36 3.5 Discussions and Comparison to Leap-Frog 42 3.5.1 Discussions 42 3.5.2 Comparison to Leap-Frog 45 3.6 Summary 51 Chapter 4 Preliminaries to Cost-Aware Path Planning 53 4.1 Related works 54 4.2 Sampling based path planning 56 4.3 Cross entropy method 59 4.3.1 Cross entropy based path planning 63 Chapter 5 Fast Cost-Aware Path Planning using Stochastic Optimization 65 5.1 Problem formulation 66 5.2 Issues with sampling-based path planning for complex terrains or high dimensional spaces 68 5.3 Cost-Aware path planning (CAPP) 73 5.3.1 CE Extend 75 5.4 Analysis of CAPP 81 5.4.1 Probabilistic Completeness 81 5.4.2 Asymptotic optimality 83 5.5 Simulation and experimental results 84 5.5.1 (P1) Cost-Aware Navigation in 2D 85 5.5.2 (P2) Complex Terrain Navigation 88 5.5.3 (P3) Humanoid Motion Planning 96 5.6 Summary 103 Chapter 6 Effcient Informative Path Planning 105 6.1 Problem formulation 106 6.2 Cost-Aware informative path planning (CAIPP) 109 6.2.1 Overall procedure 110 6.2.2 Update Bound 112 6.2.3 CE Estimate 115 6.3 Analysis of CAIPP 118 6.4 Simulation and experimental results 120 6.4.1 Single robot informative path planning 120 6.4.2 Multi robot informative path planning 122 6.5 Summary 125 Chapter 7 Conclusion and Future Work 129 Appendices 131 Appendix A Proof of Theorem 1 133 Appendix B Proof of Theorem 2 135 Appendix C Proof of Theorem 3 137 Appendix D Proof of Theorem 4 139 Appendix E Dubins' curve 141 Bibliography 147 초 록 163Docto

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Fast multipole networks

Two prerequisites for robotic multiagent systems are mobility and communication. Fast multipole networks (FMNs) enable both ends within a unified framework. FMNs can be organized very efficiently in a distributed way from local information and are ideally suited for motion planning using artificial potentials. We compare FMNs to conventional communication topologies, and find that FMNs offer competitive communication performance (including higher network efficiency per edge at marginal energy cost) in addition to advantages for mobility

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications