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1	Development of an acoustic emission waveguide-based system for monitoring of rock slope deformation mechanisms Codeglia, Daniela January 2017 (has links) Hundreds of thousands of landslides occur every year around the world impacting on people's lives. Monitoring techniques able to foresee imminent collapse and provide a warning in time useful for action to be taken are essential for risk reduction and disaster prevention. Acoustic emission (AE) is generated in soil and rock materials by rearrangement of particles during displacement or increasing damage in the microstructure preceding a collapse; therefore AE is appropriate for estimation of slope deformation. To overcome the high attenuation that characterise geological materials and thus to be able to monitor AE activity, a system called Slope ALARMS that makes use of a waveguide to transmit AE waves from a deforming zone to a piezoelectric transducer was developed. The system quantifies acoustic activity as Ring Down Count (RDC) rates. In soil applications RDC rates have been correlated with the rate of deformation, however, the application to rock slopes poses new challenges over the significance of the measured AE trends, requiring new interpretation strategies. In order to develop new approaches to interpret acoustic emission rates measured within rock slopes, the system was installed at two trial sites in Italy and Austria. RDC rates from these sites, which have been measured over 6 and 2.5 years respectively, are analysed and clear and recurring trends were identified. The comparison of AE trends with response from a series of traditional instruments available at the sites allowed correlation with changes in external slope loading and internal stress changes. AE signatures from the limestone slope at the Italian site have been identified as generated in response to variations in the groundwater level and snow loading. At the conglomerate slope in Austria, AE signatures include the detachment of small boulders from the slope surface caused by the succession of freeze-thaw cycles during winter time. Consideration was also given to laboratory testing of specific system elements and field experiments. A framework towards strategies to interpret measured acoustic emission trends is provided for the use of the system within rock slopes.
2	Adaptive Warning Field System Vaidya, Varun, Bheemesh, Kushal January 2017 (has links) This thesis is based on the work carried out in the field of safety systems for Autonomous Guided Vehicles(AGV). With autonomous vehicles being more prominent today, safe traversing of these is a major concern. The same is true for AGVs working in industry environment like forklift trucks etc. Our work applies to industrial robots. The method described here is developed by closely following an algorithm developed for safe traversing of a robot using a warning field. The report describes the literature review with work related to the safe traversing, path planning and collision avoidance in robots. The next part is dedicated to describing the methodology of implementation of the Adaptive Warning Field Method and the Dynamic Window Approach. The evaluation of the Adaptive Warning Method with the previous developed Warning Field Methods is done and test cases are designed to test the working of the designed method. Vrep simulation environment and Industrial data is used to run a simulation of the robot using the method developed in this work. We find that the method performs better compared to the previous methods in the designed scenarios. Lastly we conclude the report with the future work that can be carried out to improve and extend the algorithm. Automated Guided Vehicles (AGVs) Adaptive Warning Field Collision Avoidance Dynamic Window Approach(DWA) F45 Static Protection and Warning Fields. Computer Systems Datorsystem Robotics Robotteknik och automation
3	Empirical Data Based Predictive Warning System on an Automated Guided Vehicle / Empiriskt databaserat predikterande varningsystem för självkörande truckar Blåberg, Anton, Lindahl, Gustav January 2022 (has links) An Automated Guided Vehicle (AGV) must follow protective regulations to avoidcrashing into people when autonomously driving in industries. These safety norms require AGVs to enable protective fields, which perform hard braking when objects enter aspecific area in front of the vehicle. Warning fields, or warning systems, are similar fieldsthat decrease the speed of the AGV before objects enter the protective fields to enable asteadier driving. Today at Toyota Material Handling Manufacturing Sweden (TMHMS),warning systems have been implemented but the systems are too sensitive to objects outside of the AGVs path.The purpose of this thesis is to develop a predictive warning system based on empiricaldata from previous driving scenarios. By storing previous positions, the warning systemcould estimate a trajectory based on simple statistics and deploy speed limiting decisionsif objects appear in the upcoming predicted path.The predictive warning system was compared to the current warning system and adeactivated warning system setup in driving performance and driving dynamics. Performance was measured by measuring time to finish an industry-like test track and dynamicswas subjectively rated from a group of experienced AGV developers from TMHMS. Results showed that a predictive warning system drove the test track faster and with betterdynamics than the current warning system and the no warning system setup.Key findings are that a predictive warning system based on empirical data performedbetter in most cases but has some extra requirements to function. Firstly, the method require the AGV to mostly drive on previously driven paths to produce good results. Secondly the warning system requires a somewhat powerful on board computer to handlethe computations. Finally, the warning system requires spatial awareness of pose for thevehicle, as well as structure and shape for deployed protective fields. AGV Automated Guided Vehicles Autonomous Mobile Robots LiDAR Warning Field Warning System Collision Avoidance Braking System Robotics Autonomous Vehicles Path Predictive Position Forecasting Speed Regulation Decision Making Protective Field Protective System Industry 4.0 AI Självkörande truckar Varningsfält Varningssystem Säkerhetsfält Säkerhetssystem Industri 4.0 Automatiskt inbromsning Positionsprognos Beslutsfattande Embedded Systems Inbäddad systemteknik Robotics Robotteknik och automation Computer Systems Datorsystem Vehicle Engineering Farkostteknik

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