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

Points of Interest Coverage with Connectivity Constraints using Wireless Mobile Sensors

Part 7: Network Topology ConfigurationInternational audienceThe coverage of Points of Interest (PoI) is a classical requirement in mobile wireless sensor applications. Optimizing the sensors self-deployment over a PoI while maintaining the connectivity between the sensors and the sink is thus a fundamental issue. This article addresses the problem of autonomous deployment o f mobile sensors that need to cover a predefined PoI with a connectivity constraints and provides the solution to it using Relative Neighborhood Graphs (RNG). Our deployment scheme minimizes the number of sensors used for connectivity thus increasing the number of monitoring sensors. Analytical results, simulation results and real implementation are provided to show the efficiency of our algorithm

Connectivity Preservation and Coverage Schemes for Wireless Sensor Networks

International audienceIn this paper, we consider the self-deployment of wireless sensor networks. We present a mechanism which allows to preserve network connectivity during the deployment of mobile wireless sensors. Our algorithm is localized and is based on a subset of neighbors for motion decision. Our algorithm maintains a connected topology regardless of the direction chosen by each sensor. To preserve connectivity, the distance covered by the mobile nodes is constrained by the connectivity of the node to its neighbors in a connected subgraph like the relative neighborhood graph (RNG). We show the connectivity preservation property of our algorithm through analysis and present some simulation results on different deployment schemes such as full coverage, point of interest coverage or barrier coverage

A Swarm Robotic Approach to Inspection of 2.5 D Surfaces in Orbit

Robotic inspection offers a robust, scalable, and flexible alternative to deploying fixed sensor networks or humaninspectors. While prior work has mostly focused on single robot inspections, this work studies the deployment of a swarm ofinspecting robots on a simplified surface of an in-orbit infrastructure. The robots look for points of mechanical failure and inspectthe surface by assessing propagating vibration signals. In particular, they measure the magnitude of acceleration they sense ateach location on the surface. Our choice for sensing and analyzing vibration signals is supported by the established position ofvibration analysis methods in industrial infrastructure health assessment. We perform simulation studies in Webots, a physicsbased robotic simulator, and present a distributed inspection algorithm based on bio-inspired particle swarm optimization andevolutionary algorithm niching techniques to collectively localize an a priori unknown number of mechanical failure points. Toperform the vibration analysis and obtain realistic acceleration data, we use the ANSYS multi-physics simulation software andmodel mechanical failure points as vibration sources on the surface. We deploy a robot swarm comprising eight robots of 10-cmsize that use a bio-inspired inchworming locomotion pattern. The swarm is deployed on 2.5D (that is curved 2D) cylindricalsurfaces with and without obstacles to investigate the robustness of the algorithm in environments with varying geometric complexity. We study three performance metrics: (1) proximity of the localized sources to their ground truth locations, (2) time tolocalize each source, and (3) time to finish the inspection task given an 80% surface coverage threshold. Our results show thatthe robots accurately localize all the failure sources and reach the coverage threshold required to complete the inspection. Thiswork demonstrates the viability of deploying robot swarms for inspection of potentially complex 3D environments.<br/