Autonomous deployment and repair of a sensor network using an unmanned aerial vehicle

We describe a sensor network deployment method using autonomous flying robots. Such networks are suitable for tasks such as large-scale environmental monitoring or for command and control in emergency situations. We describe in detail the algorithms used for deployment and for measuring network connectivity and provide experimental data we collected from field trials. A particular focus is on determining gaps in connectivity of the deployed network and generating a plan for a second, repair, pass to complete the connectivity. This project is the result of a collaboration between three robotics labs (CSIRO, USC, and Dartmouth.)

OFRD:Obstacle-Free Robot Deployment Algorithms for Wireless Sensor Networks

[[abstract]]Node deployment is an important issue in wireless sensor networks (WSNs). Sensor nodes should be efficiently deployed in a predetermined region in a low cost and high coverage quality manner. Random deployment is the simplest way for deploying sensor nodes but may cause the unbalanced deployment and therefore increase the hardware cost. This paper presents an efficient obstacle-free robot deployment algorithm, called OFRD which involves the design of node placement policy, snake-like movement policy, and obstacle handling rules. By applying the proposed OFRD, the robot rapidly deploys near-minimal number of sensor nodes to achieve full sensing coverage even though there exist unpredicted obstacles. Performance results reveal that OFRD outperforms the existing robot deployment mechanism in terms of power conservation and obstacle resistance, and, therefore achieves a better deployment performance.[[incitationindex]]Y[[conferencetype]]國際[[conferencedate]]20070311~20070315[[conferencelocation]]Kowloon, Hong Kon

Multiple Target Discovery and Coverage with Mobile Wireless Sensors

International audienceEnvironmental monitoring has become a typical application of wireless sensor networks. The concept of monitoring certain points in the sensor field instead of the whole field area helps in reducing the costs of the deployment and improving the performance in terms of coverage. However, the problems of environment exploration, multiple target coverage and connectivity preservation are still solved separately and there are no works that combine the aforementioned problems into a single deployment scheme. In this work, we present a novel approach for mobile sensor deployment, where we combine the environment exploration with with network connectivity preservation and multiple target coverage. We examine the performance of our scheme through extensive simulation campaigns

Energy-Efficient Mechanisms for Coverage Recovery in WSNs

[[abstract]]In wireless sensor networks (WSNs), coverage of the monitoring area represents the quality of service (QoS) related to the surveillance. In literature, a number of studies developed robot deployment and patrol algorithms. However, the efficiency of existing repair algorithms can be further improved in terms of time and energy consumption. Moreover, existing repair algorithms did not consider the existence of obstacles and the constraint of limited energy of the robot. This paper presents novel tracking mechanism and robot repairing algorithm for maintaining the coverage quality for a given WSN. Without the support of location information, the tracking mechanism leaves the robot's foot marks such that sensors that are nearby the failure region can learn better routes for sending repairing requests to the robot. Upon receiving several repairing request messages, the robot applies the proposed repairing algorithm to establish an optimal route that passes through all failure regions with minimal overhead in terms of the required time and power consumption. In addition, the proposed repairing algorithm also considers the remaining energy of the robot so that the robot can be back to home for recharging energy and overcome the unpredicted obstacles. Performance study reveals that the developed protocol can efficiently maintain the coverage quality while the required time and energy consumption are significantly reduced.[[conferencetype]]國際[[conferencedate]]20080806~20080808[[iscallforpapers]]Y[[conferencelocation]]Crete Island, GREEC

Adaptive Deployment Scheme for Mobile Relays in Substitution Networks

International audienceWe present how the mobility of routers impacts the performance of a wireless substitution network. To that end, we simulate a scenario where a wireless router moves between three static nodes, a source and two destinations of UDP traffic. Specifically, our goal is to deploy or redeploy the mobile relays so that application-level requirements, such as data delivery or latency, are met. Our proposal for a mobile relay achieves these goals by using an adaptive approach to self-adjust their position based on local information. We obtain results on the performance of end-to-end delay, jitter, loss percentage, and throughput under such mobility pattern for the mobile relay. We show how the proposed solution is able to adapt to topology changes and to the evolution of the network characteristics through the usage of limited neighborhood knowledge

Intelligent Trajectory Design for RIS-NOMA aided Multi-robot Communications

A novel reconfigurable intelligent surface-aided multi-robot network is proposed, where multiple mobile robots are served by an access point (AP) through non-orthogonal multiple access (NOMA). The goal is to maximize the sum-rate of whole trajectories for multi-robot system by jointly optimizing trajectories and NOMA decoding orders of robots, phase-shift coefficients of the RIS, and the power allocation of the AP, subject to predicted initial and final positions of robots and the quality of service (QoS) of each robot. To tackle this problem, an integrated machine learning (ML) scheme is proposed, which combines long short-term memory (LSTM)-autoregressive integrated moving average (ARIMA) model and dueling double deep Q-network (D$^{3}$QN) algorithm. For initial and final position prediction for robots, the LSTM-ARIMA is able to overcome the problem of gradient vanishment of non-stationary and non-linear sequences of data. For jointly determining the phase shift matrix and robots' trajectories, D$^{3}$QN is invoked for solving the problem of action value overestimation. Based on the proposed scheme, each robot holds a global optimal trajectory based on the maximum sum-rate of a whole trajectory, which reveals that robots pursue long-term benefits for whole trajectory design. Numerical results demonstrated that: 1) LSTM-ARIMA model provides high accuracy predicting model; 2) The proposed D$^{3}$QN algorithm can achieve fast average convergence; 3) The RIS with higher resolution bits offers a bigger sum-rate of trajectories than lower resolution bits; and 4) RIS-NOMA networks have superior network performance compared to RIS-aided orthogonal counterparts

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

Localization, Visualization And Evacuation Guidance System In Emergency Situations

Urban search and rescue is needed for a variety of emergencies or disasters, including tornadoes, floods, dam failures, technological accidents, and terrorist activities. The efficiency to save people is becoming very important. With the development of the technology, people are trying to find a better way to help people get out of the dangerous places as soon as possible. DIORAMA system has been proposed to help with this problem and turns out very successful on improving efficiency during emergency situation. However, the current DIORAMA system is not perfect for all scenarios, for example, there are some outdoor environments do not support GPS service. Also, the RFID reader is very heavy for responders to carry and the indoor environment is not applicable for DIORAMA system. Besides, there are lack of forensic visualization toolkits that are able to help the incident commander analyze the responders’ behavior and efficiency. In this project, we propose a Localization, Visualization and Evacuation Guidance System in Emergency Situations. The functionalities in this system include localization in outdoor environments using BLE. Besides, for outdoor environments, some forensic visualization toolkit that can help the responder analyze the responders’ behavior with the capability of visualization and representation of data clearly as well as replay the task, detect anomalies and visualize the anomalies clearly is also provided in improving the efficiency and organization in the future task. In addition, the system also includes an indoor localization, navigation guidance and visualization system that provides guidance for people to exit a dangerous building as soon as possible. This system is able to localize the position of evacuees, and construct the exit path that helps reduce the escape time as well as provide a navigation guidance that is able to guide the user to the exit. In addition, an analyst simulation application is provided to simulate the evacuees in a building and evaluate the evacuation time for evacuees given specific path generation algorithm