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Unmanned ground vehicles (UGVs) have great potential in the application of both civilian and military fields, and have become the focus of research in many countries. Environmental perception technology is the foundation of UGVs, which is of great significance to achieve a safer and more efficient performance. This article firstly introduces commonly used sensors for vehicle detection, lists their application scenarios and compares the strengths and weakness of different sensors. Secondly, related works about one of the most important aspects of environmental perception technology—vehicle detection—are reviewed and compared in detail in terms of different sensors. Thirdly, several simulation platforms related to UGVs are presented for facilitating simulation testing of vehicle detection algorithms. In addition, some datasets about UGVs are summarized to achieve the verification of vehicle detection algorithms in practical application. Finally, promising research topics in the future study of vehicle detection technology for UGVs are discussed in detail.

Ultra-wideband (UWB) technology is one of the most promising wireless communication technologies. Examples of UWB applications include, among others, radiocommunication devices and location systems, due to their operating range, ability to work in outdoor environments, and resistance to multipath effects. This article focuses on the use of UWB technology in constructing a guide localization system for an unmanned ground vehicle (UGV), which is one of the stages of implementing a &ldquo, follow me&rdquo, system. This article describes the complete process of UWB signal processing from its acquisition, methods of filtering, and obtained results, to determining the location of the guide. This article examines the possibility of using modified versions of localization algorithms for determining the guide&rsquo, s location, including trilateration, methods of nonlinear programming, and a geometric algorithm proposed by us. The innovation of this study consists in the implementation of an algorithm that changes the selection of equations (mathematical model) for determining location based on the number of available measurements from UWB sensors.

In order to continue the Unmanned Tactical Autonomous Control and Collaboration (UTACC) program, an accurate understanding of the current unmanned vehicles (UxVs) available on the commercial market is required. This thesis used site visits, conference attendance, trade shows, and online databases to evaluate and rank both unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). This thesis identified 10 out of 46 UAVs and five UGVs that could be quick-wins for the Marine Corps if adopted. These identified platforms received the highest scores based on five measures of effectiveness (MOEs): technology readiness level (TRL), mission capability, interdependence, modularity, and security. This thesis also addressed the need to evaluate systems based on their level of interdependence instead of level of autonomy, acknowledging the importance of human-machine teaming. CRUSER https://hdl.handle.net/10945/60380 Captain, United States Marine Corps Captain, United States Marine Corps Approved for public release; distribution is unlimited.

Every year, Alpine experiences a considerable number of avalanches causing danger to visitor and saviors, where most of the existing techniques to mitigate the number of fatalities in such hostile environments are based on a non-collaborative approach and is time- and effort-inefficient. A recently completed European project on Smart collaboration between Humans and ground-aErial Robots for imProving rescuing activities in Alpine environments (SHERPA) has proposed a novel collaborative approach to improve the rescuing activities. To be an integral part of the SHERPA framework, this paper considers deployment of an air-ground collaborative wireless network (AGCWN) to support search and rescue (SAR) missions in hostile alpine environments. We propose a network infrastructure for such challenging environments by considering the available network components, hostility of the environments, scenarios, and requirements. The proposed infrastructure also considers two degrees of quality of service, in terms of high throughput and long coverage range, to enable timely delivery of videos and images of the long patrolled area, which is the key in any searching and rescuing mission. We also incorporate a probabilistic search technique, which is suitable for collaborative search assuming AGCWN infrastructure for sharing information. The effectiveness of the proposed infrastructure and collaborative search technique, referred to as Collab-SAR , is demonstrated via a series of computer simulations. The results confirm the effectiveness of the proposal.

Autonomous robotic systems often encounter varying degrees of uncertainty. Characteristics of an environment or mission, such as the definition of a terrain, the presence of an attacker, or the necessary sub-goals may have dramatic impacts on mission performance. Guaranteeing reliable execution demands an analysis of these uncertainties in order to ensure some form of robust operation, such as continual performance in the presence of failures. In this thesis, we present contributions related to robust operations of multi-robot coordination and autonomous exploration and an in-depth analysis of LiDAR-related uncertainties.

Historiskt har soldater till fots burit sin personliga utrustning till fots. Den övriga utrustning som soldaten behövde transporterades ofta i vagnar dragna av olika dragdjur. Då stridstempot och framförallt framryckningshastigheten har ökat, har behovet av att bära med sig all nödvändig utrustning ökat. I takt med att nya system tillförts, har därmed också den burna vikten för den enskilde soldaten ökat. Undersökningen har genomförts som en komparativ studie av olika typer av obemannade markfarkoster, så kallade UGV-system, genom att deras möjligheter och begränsningar har analyserats och jämförts utifrån de krav som ställs av scenariot, och av den militära användaren, vid lösandet av en specifik taktisk uppgift. Kriterierna för jämförelse har med hjälp av konceptet militär nytta, framtaget av Andersson et al (2015), tagits fram ur scenariot. Studien kan konstatera att den militära nyttan med dessa UGV-system är att soldaternas egen rörlighet och uthållighet ökar, samtidigt som den skaderisk som tunga bördor innebär minskar. En soldat som inte är utmattad efter att ha burit tung utrustning har en högre stridsberedskap och agerar med större skärpa. Förbandens operativa rörlighet och uthållighet ökar också och beroende på vilket UGV-system som används återfinns olika grader av militär nytta. Historically, soldiers on foot have carried their personal equipment. Other equipment that the soldier needed was often transported in wagons drawn by different beasts of burden. As the high operational tempo, and above all, forward speed has increased, the need to carry all necessary equipment also has grown. And, as new systems have been added, the load to carry for the individual soldier has thus increased. The survey has been conducted as a comparative study of different types of unmanned ground vehicles, so-called UGV systems, by analyzing their possibilities and limitations based on the requirements of the scenario and also the requirements by the military user in solving a specific tactical task. The criteria for comparison have been developed from the scenario using the concept of military utility, developed by Andersson et al. (2015). The study concludes that the military benefits connected to the UGV systems are that the individual mobility and endurance of the soldiers increases, and that the risk of injuries from carrying heavy loads decreases. A soldier not exhausted from carrying heavy loads has a higher combat preparedness and acts with greater focus. The operational mobility and endurance of the unit also increases and, depending on which UGV systems are used, different degrees of military benefit are to be found.

Bu çalışmada, hareketli platform olarak kullanılan insansız kara araçlarının seyir halindeyken rotalarıüzerindeki bir kısım hareketli nesnelerin tespiti için görüntü işleme tabanlı olarak geliştirilen ikiyardımcı sistemin performans karşılaştırması yapılmıştır. Yardımcı sistemlerin geliştirilmesinde küreselkonumlandırma sisteminden sağlanan coğrafi konum verileri kullanılmıştır. Çalışmada coğrafikonumlarına göre modelleri çıkartılan arka plan görüntüleri referans model ve anlık model olarak ikifarklı şekilde incelenmiştir. Referans modeller varsayılan arka plan (hareketli nesne içermeyen arkaplan) görüntülerinden elde edilirken, anlık modeller ise gerçek zamanlı arka plan görüntülerinden eldeedilmiştir. Karşılaştırma işlemi sonucu belirlenen siluetler yapay sinir ağları kullanılaraksınıflandırılmıştır. Sınıflandırma için 5 giriş ve 3 çıkışlı bir yapay sinir ağı (YSA) mimarisi uygulanmıştır.Mimarinin son katmanında softmax fonksiyonu kullanılmıştır. Yapay sinir ağında her bir çıkış yaya,otomobil ve bisikletli olarak 3 farklı nesne sınıfını temsil etmektedir. İlk yöntemde iki boyutlu görüntüçakıştırma yöntemi kullanılarak referans ve anlık görüntü çerçeveleri hizalanmıştır. Çerçeve farkıyöntemi ile aynı hizaya getirilen çerçevelerin aritmetik farkları alınarak görüntüye giren dinamiknesnelerin siluetleri elde edilmiştir. İkinci yöntemde arka plan görüntüleri bloklara bölünmüştür.Model oluşturmak için ortalama parlaklık değerleri kullanılmıştır. Referans ve anlık modellerinkarşılaştırma işlemi bloklar arasındaki Öklid uzaklıkları hesaplanarak gerçekleştirilmiştir. Yapılandeneysel çalışmalarda; uzaklığa bağlı olarak %94 ile %71 arası doğru sınıflandırma oranları eldeedilmiştir., In this study, performance comparison of two assistant systems were developed on the basis of imageprocessing for detecting moving objects along the route of unmanned ground vehicles used as mobileplatform. The geographical position data provided from global positioning system was used to developon the assistance systems. In the study, modeled background images according to their geographicallocations are handled in two different ways as reference model and instant model. Reference modelsare derived from default background (background without moving objects), and instant models arederived from real-time background images. The results of the comparison are classified using artificialneural network techniques. In the first method, the reference and instant frames are aligned using two-dimensional image registration methods. By subtracting aligned frames with the frame differencingmethod, the silhouettes of the moving objects in the scene are obtained. In the second method, thebackground images are divided into blocks. The average gray-level values are used to create the model.The comparison of the reference and instant models are performed by calculating the Euclideandistances between the blocks. For the classification of the silhouettes 5-input and 2-output artificial neural network (ANN) architecture is applied. In this artificial neural network, each output represents adifferent class of objects as pedestrians, cars and bikes. In experimental studies; the farthest distancesdetermined with a success rate of 85% were determined.

[Resumen] El despliegue de plataformas robóticas como apoyo a la gestión de situaciones de emergencia constituye un reto que persigue mejorar la eficiencia en misiones de búsqueda y rescate. Este artículo propone un planificador estratégico para el rescate de víctimas mediante un equipo de robots terrestres. Este sistema inteligente permitirá planificar las trayectorias para acceder a las víctimas de acuerdo con su ubicación y prioridad de asistencia médica (triaje). Para la planificación se propone una nueva variante del algoritmo “fast marching method” (FMM). En este trabajo se ofrecen resultados preliminares mediante un ejemplo de aplicación en condiciones simuladas. [Abstract] The deployment of robotic platforms in support of emergency management is a challange that seeks to improve efficiency in search and rescue missions. This paper proposes a strategic planner for the rescue of victims with a team of ground robots. The purpose of this intelligent system is planning the routes to access a number of victims according to their location and priority of medical assistance (i.e., triage). In particular, this paper offers work in progress regarding a new anisotropic variant of the fast marching method (FMM). Furthermore, preliminary results illustrate the application under simulated conditions. Ministerio de Economía, Industria y Competitividad; DPI2015-65186-R Ministerio de Economía, Industria y Competitividad; BES-2016-077022

This paper describes the design and implementation of a controller to track the desired heading angle for an unmanned ground vehicle (UGV) considering the limits on rotation of steering wheel and steering motor rate. The well-known �bicycle model� approximation, that considers the vehicle slip angle and ground-wheel interaction, has been used. In this work, combined closed loop control for steering motor and heading angle of the vehicle has been considered for better accuracy. The challenge in designing this control system is to include the actuator dynamics as the response time to steer the front wheel is in the same order as that of the heading angle dynamics of the vehicle. Experiments have been conducted, analysis of data collected is presented and the resulting mathematical representation is explained in detail. Results from both simulation and experimental implementation are also compared. It has been found that the vehicle controller can be tuned effectively to achieve the desired heading angle changes up to twenty degrees within three seconds when the vehicle is moving at a speed of 1.4 m/sec. � 2015, The Korean Society of Automotive Engineers and Springer-Verlag Berlin Heidelberg.

Latency is a common issue found in robotics teleoperation that is not currently addressed in simulation. This study examined the effects of latency on operator performance for a robot teleoperation navigation task. Operators used a Logitech gamepad controller to tele-operate a robot through both a simulated environment and real world environment. Both environments had the same dimensions and provided a path with obstacles the participant had to navigate. Participants performed this navigation task under three latency conditions, zero, low and high. Completion time, number of collisions, NASA-TLX, System Usability Survey, and User Experience survey were collected and participant performance compared for all latency conditions across the simulated and real-world environments. Results indicated a significant difference in participant performance between the simulated and real-world scenarios.