The estimation of the pose of a differential drive mobile robot from noisy odometer, compass and beacon distance measurements is studied. The estimation problem, which is a state estimation problem with unknown input, is reformulated into a state estimation problem with known input and a process noise term. A heuristic sensor fusion algorithm solving this state-estimation problem is proposed and compared with the extended Kalman filter solution and the Particle Filter solution in a simulation experiment. https://doi.org/10.4018/IJAIML.2020010101 https://www.linkedin.com/in/john-bolte-0856134/
Poster presentation on conference Alice and Eve 2020.
MULTIFILE
To better control the growing process of horticulture plants greenhouse growers need an automated way to efficiently and effectively find where diseases are spreading.The HiPerGreen project has done research in using an autonomous quadcopter for this scouting. In order for the quadcopter to be able to scout autonomously accurate location data is needed. Several different methods of obtaining location data have been investigated in prior research. In this research a relative sensor based on optical flow is looked into as a method of stabilizing an absolute measurement based on trilateration. For the optical flow sensor a novel block matching algorithm was developed. Simulated testing showed that Kalman Filter based sensor fusion of both measurements worked to reduce the standard deviation of the absolute measurement from 30 cm to less than 1 cm, while drift due to dead-reckoning was reduced to a maximum of 11 cm from over 36 cm.
The traffic safety of cyclists is under pressure. The number of fatalities and injuries is increasing, and the number of single-bicycle accidents is on the rise. However, from a traffic safety perspective, the most concerning trend is the growing number of incidents between motorized vehicles and cyclists. In addition to infrastructural solutions, such as more segregated and wider bike lanes, both industry and government are exploring technological developments to better safeguard cyclist safety. One of the technological solutions being considered is the use of C-V2X communication. C-V2X, Cellular Vehicle-to-X, is a technology that enables short-range signal exchanges between road users, informing them of each other's presence. C-V2X can be used, for example, to alert drivers via dedicated in-car information systems about the presence of cyclists on the road (e.g. at crossings). Although the technology and chipsets have been developed, the application of C-V2X to improve cyclist safety has not yet been thoroughly investigated. Therefore, HAN, Gazelle, and ARK Infomotives are researching the impact of C-V2X (on cyclist safety). Using advanced simulations with a digital twin in an urban environment and rural environment, the study will analyze how drivers respond to cyclist presence signals and determine the maximum penetration rate of ‘connected’ cyclists. Based on this, a pilot study will be conducted in a controlled environment on HAN terrain to validate the direction of the simulation results. The project aligns with the Missiegedreven Innovatiebeleid and the KIA Sleuteltechnologieën, specifically within application of digital and information technologies. This proposal aligns with the innovation domain of Semiconductor Technologies by applying advanced sensor and digital connectivity solutions to enhance cyclist safety. The project fits within the theme of Sleuteltechnologieën en Duurzame Materialen of the strategic research agenda of the VH by utilizing digital connectivity, sensor fusion, and data-driven decision-making for safer mobility solutions.
Fontys University of Applied Science’s Institute of Engineering, and the Dutch Institute for Fundamental Energy Research (DIFFER) are proposing to set up a professorship to develop novel sensors for fusion reactors. Sensors are a critical component to control and optimise the unstable plasma of Tokamak reactors. However, sensor systems are particularly challenging in fusion-plasma facing components, such as the divertor. The extreme conditions make it impossible to directly incorporate sensors. Furthermore, in advanced reactor concepts, such as DEMO, access to the plasma via ports will be extremely limited. Therefore, indirect or non-contact sensing modalities must be employed. The research group Distributed Sensor Systems (DSS) will develop microwave sensor systems for characterising the plasma in a tokamak’s divertor. DSS will take advantage of recent rapid developments in high frequency integrated circuits, found, for instance, in automotive radar systems, to develop digital reflectometers. Access through the divertor wall will be achieved via surface waveguide structures. The waveguide will be printed using 3D tungsten printing that has improved precision, and reduced roughness. These components will be tested for durability at DIFFER facilities. The performance of the microwave reflectometer, including waveguides, will be tested by using it to analyse the geometry and dynamics of the Magnum PSI plasma beam. The development of sensor-based systems is an important aspect in the integrated research and education program in Electrical Engineering, where DSS is based. The sensing requirements from DIFFER offers an interesting and highly relevant research theme to DSS and exciting projects for engineering students. Hence, this collaboration will strengthen both institutes and the educational offerings at the institute of engineering. Furthermore millimeter wave (mmWave) sensors have a wide range of potential applications, from plasma characterisation (as in this proposal) though to waste separation. Our research will be a step towards realising these broader application areas.
Traditioneel worden robots voornamelijk ingezet in gestructureerde, afgeschermde en voorspelbare omgevingen zoals fabrieken en magazijnen. Door technologische ontwikkelingen kunnen robots ook steeds beter in ongestructureerde en complexere omgevingen opereren, soms zelfs tussen mensen en dieren. Inspectierobots, verkenningsrobots, voederrobots of fruitplukrobots doen steeds vaker repeterend, vermoeiend of gevaarlijk werk. Ze kunnen bijvoorbeeld dag en nacht inspecties uitvoeren of onvermoeibaar op de akker werken. Ook kunnen ze worden ingezet voor zoek- en reddingsoperaties in gevaarlijke gebieden, bijvoorbeeld in conflictsituaties of na een ramp. Ondanks dat er afgelopen jaren grote stappen zijn gezet op het gebied van sensoren en kunstmatige intelligentie, blijft het een uitdaging om een robot volledig autonoom, dus zonder menselijke operator, te laten werken in een complexe omgeving. Eén uitdaging zit in het slim combineren van de verschillende sensoren om een goed beeld van de omgeving en van zijn eigen positie in die omgeving te creëren. Als dit niet goed lukt, dan moet de robot alsnog worden geholpen door een menselijke operator. Een robot gebruikt sensoren om te bepalen waar hij is. Huidige sensoren hebben echter tekortkomingen en maken meetfouten. Sensorfusie is het combineren van data uit verschillende sensoren om daarmee een betere schatting te doen. Het consortium heeft ervaring met het ontwikkelen van autonome robots en heeft daarbij geconstateerd dat het ontwikkelen van sensorfusie niet alleen essentieel is, maar dat het tevens uitdagend is om gestelde doelen te halen. De wens is daarom om te onderzoeken hoe we sensorfusie naar een hoger niveau kunnen brengen. In dit project analyseren en optimaliseren we de meest gebruikte methode voor het fuseren van encoders, IMUs, kompas en GNSS en vergelijken de huidige aanpak met recent ontwikkelde methodes. Met deze kennis kunnen Nederlandse technologiebedrijven voorop blijven lopen bij de ontwikkeling van autonome robots voor agrifood, inspectie, defensie en security-toepassingen.
