With an increased interest in precision agriculture, it is important to identify efficient ways to monitor soil moisture. Soil moisture can be monitored using handheld sensors, but this method is laborious and time consuming. Remote methods, such as radar systems can be used as well, but these methods require ground truth data to verify their accuracy. It becomes clear that to collect this data regularly and reliably, a mobile robotic device is necessary. This thesis proposes to implement mobile robot take soil moisture measurements with less human effort than existing methods while maintaining the same accuracy. This soil moisture data collection system uses an unmanned ground vehicle (UGV) to take measurements with position data. This system uses an actuator inserted soil moisture probe, and a radio frequency identification (RFID) sensing system that uses buried moisture sensing tags. Field testing of both measurement systems showed that the actuator-based system worked reliably.

Unmanned ground vehicles (UGVs) can be used in the military to mitigate risks taken by soldiers as well as to provide solutions to physically demanding, dull or dangerous tasks. While there are benefits of using UGVs, there are also needs and limitations that come with them. This thesis explores what the end user, a light infantry battalion in the Swedish Armed Forces, wants in terms of functions for a UGV designed for military oper- ations in urban terrain. This was done through a explorative case study with focus groups, where soldiers and officers from the 31st Ranger Battalion got to use two different UGV prototypes to complete tasks. This was followed by semi structured group discussions, where needs, limitations and requirements were explored. The collected data was then analysed by a thematic analysis approach. The results from the thematic analysis found several reoccurring opinions regarding requirements from the focus groups. The requirements were grouped into four categories; (1) Speed, (2) Use cases, (3) Image generating sensors, and (4) Autonomous functions. In conclusion, this thesis identified a total of 13 requirements within the four categories. To summarise, these requirements imply that a UGV meant for military operations in urban terrain must be able to keep up with sprinting soldiers, provide visual cover, be able to interact with nearby objects, have several high quality sensors and robust autonomous functions, allowing the soldiers to focus on other things than controlling the UGV.

Military reconnaissance and surveillance (R&S) missions are a crucial ingredient in overall mission safety and success. Proper intelligence will provide the ability to counter and neutralize enemy positions and attacks. Accurate detection and identification of threatening targets is one the driving forces behind good R&S intelligence. Understanding this ability and how it is affected by possible field conditions (i.e., motion) was the primary focus of this study. Motion is defined in the current study as the perceived forward self-motion of unmanned ground vehicle (UGV) also called optical flow. For the purpose of this examination, both optical flow and the presence of a foil were manipulated. I examined how optical flow, perceived from an on-board frontal camera on a UGV, affected target detection and identification. The interaction of optical flow and foil distraction, as well as the level of influence each independently had on target detection and identification, were the principle examinations. The effects that were originally predicted for the influence of optical flow on the visual search and identification task were not supported. Across manipulations of optical flow (i.e., present, not present), detection and identification were not significantly different, suggesting that the interruption rates of optical flow were ineffective at 29 frames per second (fps). The most interesting finding in the data set was, in fact, related to the recognition measure. Participants were asked to classify the tank in which they had detected in the environment as either a target or non-target. When under conditions of non-optical flow, participants correctly rejected a foil tank as not being their target more often than they accepted the target as their actual target. These results, however, only appeared to have had an effect in the non-optical flow condition. Further research should be conducted to properly evaluate the effects of varying frame rate interruption on the perception of optical flow. This will subsequently lead to an understanding of the phenomenon that is optical flow, and how it ultimately affects detection and identification tasks.

Advancements in the field of robotics together with an increased need for surveillance  have lead to an interest in utilizing autonomous agents  for area monitoring at sensitive installations. For this Master's thesis, an informative path planner called  Autonomous Surveillance Planner (ASP) was developed to be used with unmanned ground vehicles for area monitoring.  It discretizes an area of operations  into cells and assigns each cell an intruder probability. The planner then chooses the  optimal path by minimizing a cost function describing the probability of not finding an intruder along a path. Since the minimization is computationally costly, the computed path does not cover the entire area but instead only a small portion at a time.  The path from the ASP is then relayed to a timed elastic band local planner which adjusts  the path such that it avoids obstacles and is fast for an agent to execute, as well as computes control signals.   The algorithms were tested both in simulations and during field tests with promising results, showcasing that using unmanned ground vehicles for autonomous area monitoring has potential to be used in a real-world application. ASP was fast enough to be used in real-time  and was able to fully cover the area of operations. The local planner was computationally  demanding, but was able to avoid obstacles and make the agent follow the global path. / <p>Opponent: Samuel Ericson Andersson</p>

Autonomous robot missions in unknown environments are challenging. In many cases, the systems involved are unable to use a priori information about the scene (e.g. road maps). This is especially true in disaster response scenarios, where existing maps are now out of date. Areas without GPS are another concern, especially when the involved systems are tasked with navigating a path planned by a remote base station. Scene understanding via robots' perception data (e.g. images) can greatly assist in overcoming these challenges. This dissertation makes three contributions that help overcome these challenges, where there is a focus on the application of autonomously searching for radiation sources with unmanned aerial vehicles (UAV) and unmanned ground vehicles (UGV) in unknown and unstructured environments. The three main contributions of this dissertation are: (1) An approach to overcome the challenges associated with simultaneously trying to understand 2D and 3D information about the environment. (2) Algorithms and experiments involving scene understanding for real-world autonomous search tasks. The experiments involve a UAV and a UGV searching for potentially hazardous sources of radiation is an unknown environment. (3) An approach to the registration of a UGV in areas without GPS using 2D image data and 3D data, where localization is performed in an overhead map generated from imagery captured in the air. / Ph. D. / Autonomous robot missions in unknown environments are challenging. In many cases, the systems involved are unable to use <i>a priori</i> information about the scene (<i>e.g.</i> road maps). This is especially true in disaster response scenarios, where existing maps are now out of date. Areas without GPS are another concern, especially when the involved systems are tasked with navigating a path planned by a remote base station. Scene understanding via robots’ perception data (<i>e.g.</i> images) can greatly assist in overcoming these challenges. This dissertation makes three contributions that help overcome these challenges, where there is a focus on the application of autonomously searching for radiation sources with unmanned aerial vehicles (UAV) and unmanned ground vehicles (UGV) in unknown and unstructured environments. The three main contributions of this dissertation are: (1) An approach to overcome the challenges associated with simultaneously trying to understand 2D and 3D information about the environment. (2) Algorithms and experiments involving scene understanding for real-world autonomous search tasks. The experiments involve a UAV and a UGV searching for potentially hazardous sources of radiation is an unknown environment. (3) An approach to the registration of a UGV in areas without GPS using 2D image data and 3D data, where localization is performed in an overhead map generated from imagery captured in the air.

Den urbana miljön är en av de mest komplexa miljöer som svenska förband ska kunna strida i. Bristfällig information, tredimensionellt hot, korta stridsavstånd och civila är bara några av de utmaningar soldater ställs inför i urban miljö. Vissa av dessa utmaningar skulle kunna minskas genom nyttjande av obemannade sensorer, som skulle kunna ge chefer en tydligare lägesbild. Studien har genomförts som en komparativ fallstudie, där ett representativt flygande system har jämförts med ett markgående. Syftet med studien är att utröna vilket system har störst militär nytta. Utgångspunkt för jämförelsen är en konceptmodell för militär nytta, där systemen jämförts inom tre dimensioner; militär effektivitet, militär lämplighet samt ekonomisk överkomlighet. Utfallet av studien tyder på att det markgående systemet, UGV, har en något högre militär nytta än det flygande systemet. Vidare påvisar studien att det finns tydliga skillnader i kravuppfyllnad beroende på var och i vilken strid som systemen används. Det flygande har en tydlig fördel utanför byggnader under anfallsstrid, medan det markgående har en fördel inne i byggnader. Studien påvisar även att båda systemen bidrar med militär nytta till förband i urban miljö. / The urban environment is one of the most difficult environments that Swedish units are supposed to fight in. Inadequate information, a three-dimensional threat, close range combat and civilians are just a few of the challenges that face soldiers in urban environment. Some of these challenges could be reduced by the use of unmanned sensors, which could enhance the situational awareness. This study has been conducted as a comparative case study, where a representative aerial system has been compared with a ground system. The aim of the study is to determine which system has the highest military utility. The study is based on a concept model for military utility that has compared the systems within three dimensions; military effectiveness, military suitability and affordability. The result of the study indicates that the ground system, UGV, has a slight advantage in military utility compared to the aerial system. Further the study indicates that there are apparent differences between the systems depending on where they are used and in what combat situation. The aerial system has a clear advantage when used outside buildings and in offensive actions, whereas the ground system has an advantage inside buildings. The study also shows that both systems contributes with military utility to units in urban terrain.

This thesis project aims to learn and understand more about implementing a path planner to the unmanned ground vehicle (UGV), UGV Husky, specifically its traversability algorithm, and investigate how it could be further improved. A surrounding grid is generated around the UGV where each cell contains information connected to its traversability. The traversability filter is given this information to score how possible it is to traverse to the cell with regard to angular slope, terrain roughness, and step height. The three parameters have each a critical value that works as a limit where if one of the three parameters were to exceed the critical value then the cell would not be estimated to be traversable. The current problem is that their critical value for angular slope, step height, and terrain roughness are decided arbitrarily and mostly through simulation. To solve this problem, formulas are derived that focus on geometrical aspects of a UGV to define the limits in focus on slope and step. The formulas give threshold values applied to the code and are run in simulation. To validate this, hardware experiments are done to compare simulation and reality. This is to observe and learn if the simulations are good representations of reality and if the threshold values are correct. The results show that the thresholds are good estimations of the UGV Husky's limits. This is if one takes into consideration that other important factors are not included or known, such as the ground conditions in the actual experiments. The simulation studies also prove that Gazebo simulations are not good representations of reality to test terrain difficulties because of simplified physical representation, giving unreliable limits. Based on the successful implementation of the geometrically derived threshold values for slope and step, further work could include similarly derived threshold values for terrain roughness, and attempt to optimize the variables that are in the traversability formula. / Syftet med detta examensabete är attutveckla förståelsen av en ruttplaneringsalgoritm, specifikt dess framkomlighets analays, och kolla hur det går att förbättra den. Problemet som diskuteras i denna rapport är hur tröskelvärdena för vinkellutning, högsta steghöjd och terrängens grovhet är godtyckligt valda och i flesta fall från simuleringsmiljöer eller flera verklighetstester. För att lösa detta problem foukseras det på att utveckla en formel som endast kollar på de geometriska aspekterna av fordonets vinkelgräns och steghöjd. Denna formel blir testad genom att applicera de framräknade tröskelvärdena till simuleringsmiljön och observera ifall det stämmer att UGVn som användts (UGV Husky) har dessa begränsningar. För validering görs tester också i verkligheten för att se hur relationen mellan simulering och verklighet är. Resultaten visar att värdena är bra uppskattningar till vad UGV Husky klarar i verkligheten om man tar i åtanke att viktiga faktorer har inte tagits med exempelvis markförhållanden. Simulering i förhållande till verklighet är inte en bra representation på grund av dålig upplösning av modeleringen av UGVn vilket ger opålitliga gränser. Nästa steg skulle framöver vara att ta med terrängförhållanden i beräkningarna och optimera flera variabler i formeln.

Unmanned ground and aerial vehicles (UGVs and UAVs) have strict payload limitations, limited free space affecting on board power availability resulting in limited endurance and operational range. This limitation is exacerbated by the addition of sensors, actuators and other related equipment needed to accomplish mission objectives in diverse applications. Two energy sources are mainly available for mobile applications; batteries and fuel cells. Batteries are a relatively cheap, tested technology with good performance under varying loads. On the other hand, fuel cells offer fast and easy refueling solutions. Furthermore, preliminary studies have shown that a hybrid system can combine the advantages of both technologies offering a superior system. It is true that for most outdoors applications, payload needs, sensor suite utilization and energy requirements are apriori unpredictable. This makes proper sizing of energy storage devices and the prediction of remaining available energy rather difficult tasks. This research proposes an indirect way of improving the operational range for UAVs of Vertical Take Off and Landing (VTOLs), since the VTOL vehicle is transported to the mission site without the need to fly. The proposed gimballed platform, which will be a power source itself, rotates around two axes perpendicular to each other, allowing the VTOL to take-off and land, regardless of the position of the UGV, while securing it during transportation. The UGV can also serve as a charging station for the VTOL. Furthermore, this research proposes a Matlab Simulation tool that can simulate the energy and power demand of small to mid-sized robotic vehicles. This model will simulate the power consumption in the motors based on Skid steering, road gradient, linear and angular velocity. With the energy and power requirements estimated, a Matlab optimization tool is proposed to be used to determine the optimal configuration of a power system for mobile applications under constraints relating to capacity/runtime, weight, volume, cost, and system complexity. The configuration will be based on commercially available batteries, and fuel cells to significantly reduce cost and delivery time. The optimization tool can be used for any mobile application. Finally, a new model is proposed for the accurate prediction of battery runtime and remaining energy for single battery discharge. This model reformulates Peukert's equation and achieves higher accuracy by introducing a new concept of variable exponent which is a function of battery capacity and discharge current.

A ce jour, les pièces prototypes réalisées à partir de poudre ou de liquide n'ont pas forcement des propriétés mécaniques suffisantes ni la précision requise pour être placées dans des mécanismes fonctionnels. L'objectif de ce travail est de réaliser des mécanismes prototypes fonctionnels, c'est-à-dire capables de fonctionner sur un banc d'essais ou en service dans son milieu d'utilisation (sur un véhicule par exemple). L'approche URP "Usinage Rapide de Prototype" proposée consiste à décomposer une pièce complexe de type carter par exemple, en plusieurs strates épaisses usinées sur machine outil à commande numérique 5 axes et assemblées. Le tranchage en strates est déterminé de sorte que les entités fonctionnelles ne soient pas découpées et que l'usinage soit réalisable, y compris pour les entités à obtenir dans l'épaisseur de la pièce. Le type et la position des dispositifs de centrage et de fixation des strates sont ensuite choisis. Deux montages d'usinage originaux et une gamme d'usinage ont été conçus pour réaliser chaque strate en deux phases. Un protocole de vérification de l'usinabilité a été proposé. Un carter a été réalisé sur la machine MIKRON UCP 710 du laboratoire avec une analyse des précisions obtenues. Une pièce d'essai a été définie pour permettre l'évaluation des capabilités de la méthode.

La préparation de l'usinage de pièce de formes complexes induit des temps improductifs sur les machines UGV. Ces temps improductifs sont liés aux manques de méthodologies de préparation et aux faibles connaissances du préparateur sur le processus UGV. La compétitivité du procédé UGV passe donc par une réduction du temps de préparation afin de pouvoir répondre rapidement aux délais de fabrication. Ce mémoire porte sur la préparation à l'usinage des outillages de forge. Notre apport se traduit principalement par la mise en place d'une méthode originale de transfert de la géométrie CAO de l'outillage à une géométrie FAO du processus UGV de cet outillage. La méthode de décomposition topologique de la géométrie CAO proposée est basée sur le respect de la vitesse de coupe et la limitation des entrées/sorties matière. Des cartographies d'assistance au préparateur ont été développées pour élaborer cette décomposition. Une représentation graphique, appelée graphe de relation topologique, permet de collecter les informations obtenues à partir de la décomposition et de représenter les relations topologiques entre les différentes entités d'usinage obtenues par décomposition. Le modèle de relation topologique est construit à partir des difficultés d'usinage, d'accessibilité des surfaces à usiner et des ralentissements de vitesses d'avance. La méthode de génération du processus d'usinage des outillages est basée sur l'analyse topologique de la géométrie et associée aux séquences d'usinage standard. Un outil d'assistance, appelé performance viewer, permet d'analyser les ralentissements et le nombre d'entrées/sorties matière. Les maquettes numériques des outils d'assistance à la préparation sont illustrées pour la phase de décomposition topologique du modèle CAO de l'outillage de forge et la phase de génération de processus UGV d'un outillage de forge.