Research Trend Topic Area on Mobile Anchor Localization: A Systematic Mapping Study

Localization in a dynamic environment is one of the challenges in WSN localization involving dynamic sensor nodes or anchor nodes. Mobile anchors can be an efficient solution for the number of anchors in a 3-dimensional environment requiring more local anchors. The reliability of a localization system using mobile anchors is determined by various parameters such as energy efficiency, coverage, computational complexity, and cost. Various methods have been proposed by researchers to build a reliable mobile anchor localization system. This certainly shows the many research opportunities that can be carried out in mobile anchor localization. The many opportunities in this topic will be very confusing for researchers who want to research in this field in choosing a topic area early. However, until now there is still no paper that discusses systematic mapping studies that can provide information on topic areas and trends in the field of mobile anchor localization. A systematic Mapping Study (SMS) was conducted to determine the topic area and its trends, influential authors, and produce modeling topics and trends from the resulting modeling topics. This SMS can be a solution for researchers who are interested in research in the field of mobile anchor localization in determining the research topics they are interested in for further research. This paper gives information on the mobile anchor research area, the author who has influenced mobile anchor localization research, and the topic modeling and trend that potentially promissing research in the future. The SMS includes a chronology of publications from 2017-2022, bibliometric co-occurrence, co-author analysis, topic modeling, and trends. The results show that the development of mobile anchor localization publications is still developing until 2022. There are 10 topic models with 6 of them included in the promising topic. The results of this SMS can be used as preliminary research from the literacy stage, namely Systematic Literature Review (SLR)

Collaborative autonomy in heterogeneous multi-robot systems

As autonomous mobile robots become increasingly connected and widely deployed in different domains, managing multiple robots and their interaction is key to the future of ubiquitous autonomous systems. Indeed, robots are not individual entities anymore. Instead, many robots today are deployed as part of larger fleets or in teams. The benefits of multirobot collaboration, specially in heterogeneous groups, are multiple. Significantly higher degrees of situational awareness and understanding of their environment can be achieved when robots with different operational capabilities are deployed together. Examples of this include the Perseverance rover and the Ingenuity helicopter that NASA has deployed in Mars, or the highly heterogeneous robot teams that explored caves and other complex environments during the last DARPA Sub-T competition. This thesis delves into the wide topic of collaborative autonomy in multi-robot systems, encompassing some of the key elements required for achieving robust collaboration: solving collaborative decision-making problems; securing their operation, management and interaction; providing means for autonomous coordination in space and accurate global or relative state estimation; and achieving collaborative situational awareness through distributed perception and cooperative planning. The thesis covers novel formation control algorithms, and new ways to achieve accurate absolute or relative localization within multi-robot systems. It also explores the potential of distributed ledger technologies as an underlying framework to achieve collaborative decision-making in distributed robotic systems. Throughout the thesis, I introduce novel approaches to utilizing cryptographic elements and blockchain technology for securing the operation of autonomous robots, showing that sensor data and mission instructions can be validated in an end-to-end manner. I then shift the focus to localization and coordination, studying ultra-wideband (UWB) radios and their potential. I show how UWB-based ranging and localization can enable aerial robots to operate in GNSS-denied environments, with a study of the constraints and limitations. I also study the potential of UWB-based relative localization between aerial and ground robots for more accurate positioning in areas where GNSS signals degrade. In terms of coordination, I introduce two new algorithms for formation control that require zero to minimal communication, if enough degree of awareness of neighbor robots is available. These algorithms are validated in simulation and real-world experiments. The thesis concludes with the integration of a new approach to cooperative path planning algorithms and UWB-based relative localization for dense scene reconstruction using lidar and vision sensors in ground and aerial robots

A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles

The evolution in micro-electro-mechanical systems technology (MEMS) has triggered the need for the development of wireless sensor network (WSN). These wireless sensor nodes has been used in many applications at many areas. One of the main issues in WSN is the energy availability, which is always a constraint. In a previous research, a relocating algorithm for mobile sensor network had been introduced and the goal was to save energy and prolong the lifetime of the sensor networks using Particle Swarm Optimization (PSO) where both of sensing radius and travelled distance had been optimized in order to save energy in long-term and shortterm. Yet, the previous research did not take into account obstacles’ existence in the field and this will cause the sensor nodes to consume more power if obstacles are exists in the sensing field. In this project, the same centralized relocating algorithm from the previous research has been used where 15 mobile sensors deployed randomly in a field of 100 meter by 100 meter where these sensors has been deployed one time in a field that obstacles does not exist (case 1) and another time in a field that obstacles existence has been taken into account (case 2), in which these obstacles has been pre-defined positions, where these two cases applied into two different algorithms, which are the original algorithm of a previous research and the modified algorithm of this thesis. Particle Swarm Optimization has been used in the proposed algorithm to minimize the fitness function. Voronoi diagram has also used in order to ensure that the mobile sensors cover the whole sensing field. In this project, the objectives will be mainly focus on the travelling distance, which is the mobility module, of the mobile sensors in the network because the distance that the sensor node travels, will consume too much power from this node and this will lead to shortening the lifetime of the sensor network. So, the travelling distance, power consumption and lifetime of the network will be calculated in both cases for original algorithm and modified algorithm, which is a modified deployment algorithm, and compared between them. Moreover, the maximum sensing range is calculated, which is 30 meter, by using the binary sensing model even though the sensing module does not consume too much power compared to the mobility module. Finally, the comparison of the results in the original method will show that this algorithm is not suitable for an environment where obstacle exist because sensors will consume too much power compared to the sensors that deployed in environment that free of obstacles. While the results of the modified algorithm of this research will be more suitable for both environments, that is environment where obstacles are not exist and environment where obstacles are exist, because sensors in this algorithm .will consume almost the same amount of power at both of these environments

Z-path trajectory mechanism for mobile beacon-assisted localization in wireless sensor networks

A wireless sensor network consists of many sensors that communicate wirelessly to monitor a physical region. In many applications such as warning systems or healthcare services, it is necessary to enhance the captured data with location information. Determining the coordinates of the randomly deployed sensors is known as the problem of localization. A promising solution for statically deployed sensors is to benefit from a mobile beacon-assisted localization. The main challenge is planning an optimum path for the mobile beacon to ensure the full coverage, increase the accuracy of the estimated position and decrease the required time for localization of resource-constrained sensors. So, this research aims at developing a superior trajectory mechanism for mobile beacon-assisted localization to help unknown sensors to efficiently localize themselves. To achieve this purpose; first, a novel trajectory named Z-path is proposed to guarantee fully localized deployed sensors with higher precision since the path reduces collinear beacon positions and promises shorter localization time; second, Z-path transmission power adjustment scheme named Zpower is developed to dynamically and optimally adjust the transmission power for a reliable transmission while conserving the energy consumption for localization by mobile beacon and unknown sensors; third, Z-path obstacle-handling trajectory mechanism is designed to improve the effectiveness of the proposed path toward obstacles which obstruct the path. Finally, the proposed Z-path obstacle handling mechanism is integrated with the developed power adjustment scheme to improve the energy efficiency of the designed obstacle tolerance mechanism. The performance of the proposed trajectory is evaluated by comparing the efficiency with five benchmark trajectories in terms of localization success, accuracy, energy efficiency, time and ineffective position rate, which is a newly introduced metric by this research to measure the collinearity of the trajectories. Simulation results show that Z-path has successfully localized all 250 deployed sensors with higher precision by at least 5.88% improvement than Localization with a Mobile Anchor based on Trilateration (LMAT) trajectory and 58% improvement than random way point. It also serves as a benchmark path with 93 ineffective positions per node localization as compared with LMAT as a second efficient path by 100 collinear positions and faster trajectory for localization. Furthermore, results revealed that Z-power accomplishes better performance in terms of energy consumption as an average 34% for unknown sensors and 25% for mobile beacon than Z-path. In case of obstacle tolerance mechanism, it ensures higher localization performance in terms of accuracy, time and success around 37.5%, 13% and 11% respectively, as compared to Z-path at the presence of obstacles. The handling mechanism integrated with the power control scheme has reduced energy consumption and improved ineffective position rate compared with Z-path handling trajectory by 35.7% and 54.4%, respectively

Intertwined localization and error-resilient geographic routing for mobile wireless sensor networks

“This is a post-peer-review, pre-copyedit version of an article published in Wireless Networks. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11276-018-1836-7”Geographic routing in wireless sensor networks brings numerous inherent advantages, albeit its performance relying heavily on accurate node locations. In mobile networks, localization of the continuously moving nodes is a challenging task and location errors are inevitable and affect considerably routing decisions. Our proposal is in response to the unrealistic assumption widely made by previous geographic routing protocols that the accurate location of mobile nodes can be obtained at any time. Such idealized assumption results in under-performing or infeasible routing protocols for the real world applications. In this paper, we propose INTEGER, a localization method intertwined with a new location-error-resilient geographic routing specifically designed for mobile sensor networks even when these networks are intermittently connected. By combining the localization phase with the geographic routing process, INTEGER can select a relay node based on nodes’ mobility predictions from the localization phase. Results show that INTEGER improves the efficiency of the routing by increasing the packet delivery ratio and by reducing the energy consumption while minimizing the number of relay nodes compared to six prevalent protocols from the literature.Peer ReviewedPostprint (author's final draft