Privacy concerns can potentially make camera-based object classification unsuitable for robot navigation. To address this problem, we propose a novel object classification system using only a 2D-LiDAR sensor on mobile robots. The proposed system enables semantic understanding of the environment by applying the YOLOv8n model to classify objects such as tables, chairs, cupboards, walls, and door frames using only data captured by a 2D-LiDAR sensor. The experimental results show that the resulting YOLOv8n model achieved an accuracy of 83.7% in real-time classification running on Raspberry Pi 5, despite having a lower accuracy when classifying door-frames and walls. This validates our proposed approach as a privacy-friendly alternative to camera-based methods and illustrates that it can run on small computers onboard mobile robots.
DOCUMENT
Lab report on Lidar Mapping with Livox Mid-40 in ROS
MULTIFILE
In mobile robotics, LASER scanners have a wide spectrum of indoor and outdoor applications, both in structured and unstructured environments, due to their accuracy and precision. Most works that use this sensor have their own data representation and their own case-specific modeling strategies, and no common formalism is adopted. To address this issue, this manuscript presents an analytical approach for the identification and localization of objects using 2D LiDARs. Our main contribution lies in formally defining LASER sensor measurements and their representation, the identification of objects, their main properties, and their location in a scene. We validate our proposal with experiments in generic semi-structured environments common in autonomous navigation, and we demonstrate its feasibility in multiple object detection and identification, strictly following its analytical representation. Finally, our proposal further encourages and facilitates the design, modeling, and implementation of other applications that use LASER scanners as a distance sensor.
DOCUMENT
Twirre V2 is the evolution of an architecture for mini-UAV platforms which allows automated operation in both GPS-enabled and GPSdeprived applications. This second version separates mission logic, sensor data processing and high-level control, which results in reusable software components for multiple applications. The concept of Local Positioning System (LPS) is introduced, which, using sensor fusion, would aid or automate the flying process like GPS currently does. For this, new sensors are added to the architecture and a generic sensor interface together with missions for landing and following a line have been implemented. V2 introduces a software modular design and new hardware has been coupled, showing its extensibility and adaptability
DOCUMENT
Twirre is a new architecture for mini-UAV platforms designed for autonomous flight in both GPS-enabled and GPS-deprived applications. The architecture consists of low-cost hardware and software components. High-level control software enables autonomous operation. Exchanging or upgrading hardware components is straightforward and the architecture is an excellent starting point for building low-cost autonomous mini-UAVs for a variety of applications. Experiments with an implementation of the architecture are in development, and preliminary results demonstrate accurate indoor navigation
MULTIFILE
Het onderzoek in het artikel is geïnspireerd door de casus 'platooning' uit de Grand Cooperative Driving Challenge. Er is een PreScan®/Sumulink® model opgesteld met daarin twee auto's. De voorste auto volgt een vastgesteld snelheidsprofiel, de tweede auto volgt de eerste auto waarbij de tweede auto de snelheid van de eerste meet met behulp van een AIR-sensor. De besturing van het gaspedaal in beide auto's vindt plaats met Fuzzy Logic Control in plaats van met een klassieke regelaar. Concluderend mag worden gesteld dat in dit verkennend onderzoek gebleken is dat de Fuzzy Logic Control techniek in principe werkt.
DOCUMENT
This paper assesses wind resource characteristics and energy yield for micro wind turbines integrated on noise barriers. An experimental set-up with sonic anemometers placed on top of the barrier in reference positions is realized. The effect on wind speed magnitude, inflow angle and turbulence intensity is analysed. The annual energy yield of a micro wind turbine is estimated and compared using data from a micro-wind turbine wind tunnel experiment and field data. Electrical energy costs are discussed as well as structural integration cost reduction and the potential energy yield could decrease costs. It was found that instantaneous wind direction towards the barrier and the height of observation play an influential role for the results. Wind speed increases in perpendicular flows while decreases in parallel flow, by +35% down to −20% from the reference. The azimuth of the noise barrier expressed in wind field rotation angles was found to be influential resulted in 50%–130% changes with respect to annual energy yield. A micro wind turbine (0.375 kW) would produce between 100 and 600 kWh annually. Finally, cost analysis with cost reductions due to integration and the energy yield changes due to the barrier, show a LCOE reduction at 60%–90% of the reference value. https://doi.org/10.1016/j.jweia.2020.104206
DOCUMENT
De auto is niet meer weg te denken in onze huidige westerse maatschappij en bezet een belangrijke plaats in zowel ons economische als sociale leven. Hoewel Nederland al een van de meest verkeersveilige landen ter wereld is, waren er toch nog 811 verkeersdoden in 2006. Als we ons echter realiseren dat dit slechts een kwart is van de ruim 3200 verkeersdoden in 1972, is sindsdien al veel bereikt. De Nederlandse overheid streeft naar een verdere reductie tot minder dat 580 verkeersdoden in 2020. De daarvoor noodzakelijke verbeterde verkeersveiligheid zal voor een groot deel moeten komen uit nieuwe voertuigtechnologie die ongevallen helpt voorkomen (actieve veiligheid) en de gevolgen ervan beperkt (passieve veiligheid). Een auto veilig door het hedendaagse verkeer loodsen is geen eenvoudige taak, zeker niet onder slechte weersomstandigheden en bij complexe of onoverzichtelijke verkeerssituaties. Het is dan ook niet verwonderlijk dat bij het overgrote deel van de verkeersongevallen de oorzaak, minstens ten dele, bij een menselijke fout ligt. Intelligente voertuigsystemen, die met behulp van aan het voertuig verbonden omgevingssensoren het verkeer rond het voertuig monitoren, kunnen de bestuurder assisteren. Als er zich geen bijzonderheden voordoen is de bestuurder het meest gebaat bij informatieve- en comfortverhogende systemen. Als er een gevaarlijke situatie dreigt te ontstaan, komen de veiligheidssystemen in beeld. Naarmate de kans op een ongeval toeneemt, lijkt een grotere mate van ondersteuning (van waarschuwen, via assisteren tot interveniëren) gewenst. Vanwege hun veiligheidskritische karakter moeten actieve veiligheidssystemen voldoen aan hoge eisen ten aanzien van prestatie (hoge nauwkeurigheid), robuustheid (weersomstandigheden en wegcondities) en betrouwbaarheid. Hier liggen enorme uitdagingen in zowel het ontwerp als de evaluatie van dergelijke systemen waaraan het lectoraat Automotive control van Fontys Hogescholen door praktijkgericht onderzoek en vraaggestuurd onderwijs wil bijdragen.
DOCUMENT
In November 2019, the High Performance Greenhouse project (HiPerGreen) was nominated for the RAAK Award 2019, as one of the best applied research projects in the Netherlands. This paper discusses the challenges faced, lessons learned and critical factors in making the project into a success.
DOCUMENT
This article delves into the acceptance of autonomous driving within society and its implications for the automotive insurance sector. The research encompasses two different studies conducted with meticulous analysis. The first study involves over 600 participants involved with the automotive industry who have not yet had the opportunity to experience autonomous driving technology. It primarily centers on the adaptation of insurance products to align with the imminent implementation of this technology. The second study is directed at individuals who have had the opportunity to test an autonomous driving platform first-hand. Specifically, it examines users’ experiences after conducting test drives on public roads using an autonomous research platform jointly developed by MAPFRE, Universidad Carlos III de Madrid, and Universidad Politécnica de Madrid. The study conducted demonstrates that the user acceptance of autonomous driving technology significantly increases after firsthand experience with a real autonomous car. This finding underscores the importance of bringing autonomous driving technology closer to end-users in order to improve societal perception. Furthermore, the results provide valuable insights for industry stakeholders seeking to navigate the market as autonomous driving technology slowly becomes an integral part of commercial vehicles. The findings reveal that a substantial majority (96% of the surveyed individuals) believe that autonomous vehicles will still require insurance. Additionally, 90% of respondents express the opinion that policies for autonomous vehicles should be as affordable or even cheaper than those for traditional vehicles. This suggests that people may not be fully aware of the significant costs associated with the systems enabling autonomous driving when considering their insurance needs, which puts the spotlight back on the importance of bringing this technology closer to the general public.
DOCUMENT
