TY - JOUR A1 - Thust, M. A1 - Poghossian, Arshak A1 - Schöning, Michael Josef A1 - Naser, S. A1 - Müller-Veggian, Mattea A1 - Kordos, P. A1 - Lüth, H. T1 - Crosssensitivity of a capacitive penicillin sensor combined with a diffusion barrier JF - Proceedings : The Hague, The Netherlands, September 12 - 15, 1999 / [ed. by M. Bartek]. Vol 1. Y1 - 1999 SN - 90-76699-02-X N1 - Eurosensors ; (13, 1999, 's-Gravenhage) ; Eurosensors ; (13 : ; 1999.09.12-15 : ; The Hague) ; European Conference on Solid-State Transducers ; (13 : ; 1999.09.12-15 : ; The Hague) SP - 573 EP - 576 CY - The Hague, The Netherlands ER - TY - JOUR A1 - Thust, M. A1 - Poghossian, Arshak A1 - Schöning, Michael Josef A1 - Naser, S. A1 - Müller-Veggian, Mattea A1 - Kordos, P. A1 - Lüth, H. T1 - Cross-sensitivity of a capacitive penicillin sensor combined with a diffusion barrier JF - Proceedings : The Hague, The Netherlands, September 12 - 15, 1999 / [ed. by M. Bartek]. - Vol 1. Y1 - 1999 SN - 90-76699-02-X N1 - Eurosensors <13, 1999, 's-Gravenhage> ; Eurosensors <13, 1999, The Hague> ; European Conference on Solid-State Transducers <13, 1999, The Hague> SP - 573 EP - 576 CY - The Hague, The Netherlands ER - TY - CHAP A1 - Thurn, Laura A1 - Gebhardt, Andreas T1 - Arousing Enthusiasm for STEM: Teaching 3D Printing Technology T2 - Conference Proceedings: New Perspectives in Science Education Y1 - 2017 SN - 978-88-6292-847-2 SP - 87 EP - 92 PB - liberiauniversitaria.it CY - Padua ER - TY - CHAP A1 - Thurn, Laura A1 - Gebhardt, Andreas T1 - Strategy of Education on Materials for Students T2 - Conference Proceedings: „New Perspectives in Science Education" Y1 - 2018 SN - 978-88-6292-976-9 SP - 156 EP - 161 CY - Florence, Italy ER - TY - CHAP A1 - Thurn, Laura A1 - Balc, Nicolae A1 - Gebhardt, Andreas A1 - Kessler, Julia T1 - Education packed in technology to promote innovations: Teaching Additive Manufacturing based on a rolling Lab T2 - Modern Technologies in Manufacturing (MTeM 2017 - AMaTUC) Y1 - 2017 U6 - http://dx.doi.org/10.1051/matecconf/201713702013 SN - 2261-236X N1 - MATEC Web Conf. Volume 137, 2017 Matec Web of Conferences., 137(2017)02013 ER - TY - JOUR A1 - Thomessen, Karolin A1 - Thoma, Andreas A1 - Braun, Carsten T1 - Bio-inspired altitude changing extension to the 3DVFH* local obstacle avoidance algorithm JF - CEAS Aeronautical Journal N2 - Obstacle avoidance is critical for unmanned aerial vehicles (UAVs) operating autonomously. Obstacle avoidance algorithms either rely on global environment data or local sensor data. Local path planners react to unforeseen objects and plan purely on local sensor information. Similarly, animals need to find feasible paths based on local information about their surroundings. Therefore, their behavior is a valuable source of inspiration for path planning. Bumblebees tend to fly vertically over far-away obstacles and horizontally around close ones, implying two zones for different flight strategies depending on the distance to obstacles. This work enhances the local path planner 3DVFH* with this bio-inspired strategy. The algorithm alters the goal-driven function of the 3DVFH* to climb-preferring if obstacles are far away. Prior experiments with bumblebees led to two definitions of flight zone limits depending on the distance to obstacles, leading to two algorithm variants. Both variants reduce the probability of not reaching the goal of a 3DVFH* implementation in Matlab/Simulink. The best variant, 3DVFH*b-b, reduces this probability from 70.7 to 18.6% in city-like worlds using a strong vertical evasion strategy. Energy consumption is higher, and flight paths are longer compared to the algorithm version with pronounced horizontal evasion tendency. A parameter study analyzes the effect of different weighting factors in the cost function. The best parameter combination shows a failure probability of 6.9% in city-like worlds and reduces energy consumption by 28%. Our findings demonstrate the potential of bio-inspired approaches for improving the performance of local path planning algorithms for UAV. KW - UAV KW - Obstacle avoidance KW - Autonomy KW - Local path planning Y1 - 2023 U6 - http://dx.doi.org/10.1007/s13272-023-00691-w SN - 1869-5590 (Online) SN - 1869-5582 (Print) N1 - Corresponding author: Karolin Thomessen PB - Springer CY - Wien ER - TY - JOUR A1 - Thoma, Andreas A1 - Thomessen, Karolin A1 - Gardi, Alessandro A1 - Fisher, A. A1 - Braun, Carsten T1 - Prioritising paths: An improved cost function for local path planning for UAV in medical applications JF - The Aeronautical Journal N2 - Even the shortest flight through unknown, cluttered environments requires reliable local path planning algorithms to avoid unforeseen obstacles. The algorithm must evaluate alternative flight paths and identify the best path if an obstacle blocks its way. Commonly, weighted sums are used here. This work shows that weighted Chebyshev distances and factorial achievement scalarising functions are suitable alternatives to weighted sums if combined with the 3DVFH* local path planning algorithm. Both methods considerably reduce the failure probability of simulated flights in various environments. The standard 3DVFH* uses a weighted sum and has a failure probability of 50% in the test environments. A factorial achievement scalarising function, which minimises the worst combination of two out of four objective functions, reaches a failure probability of 26%; A weighted Chebyshev distance, which optimises the worst objective, has a failure probability of 30%. These results show promise for further enhancements and to support broader applicability. KW - Path planning KW - Cost function KW - Multi-objective optimization Y1 - 2023 U6 - http://dx.doi.org/10.1017/aer.2023.68 SN - 0001-9240 (Print) SN - 2059-6464 (Online) IS - First View SP - 1 EP - 18 PB - Cambridge University Press CY - Cambridge ER - TY - CHAP A1 - Thoma, Andreas A1 - Stiemer, Luc A1 - Braun, Carsten A1 - Fisher, Alex A1 - Gardi, Alessandro G. T1 - Potential of hybrid neural network local path planner for small UAV in urban environments T2 - AIAA SCITECH 2023 Forum N2 - This work proposes a hybrid algorithm combining an Artificial Neural Network (ANN) with a conventional local path planner to navigate UAVs efficiently in various unknown urban environments. The proposed method of a Hybrid Artificial Neural Network Avoidance System is called HANNAS. The ANN analyses a video stream and classifies the current environment. This information about the current Environment is used to set several control parameters of a conventional local path planner, the 3DVFH*. The local path planner then plans the path toward a specific goal point based on distance data from a depth camera. We trained and tested a state-of-the-art image segmentation algorithm, PP-LiteSeg. The proposed HANNAS method reaches a failure probability of 17%, which is less than half the failure probability of the baseline and around half the failure probability of an improved, bio-inspired version of the 3DVFH*. The proposed HANNAS method does not show any disadvantages regarding flight time or flight distance. Y1 - 2023 U6 - http://dx.doi.org/10.2514/6.2023-2359 N1 - AIAA SCITECH 2023 Forum, 23-27 January 2023, National Harbor, MD & Online PB - AIAA ER - TY - JOUR A1 - Thoma, Andreas A1 - Ravi, Sridhar T1 - Significance of parallel computing on the performance of Digital Image Correlation algorithms in MATLAB N2 - Digital Image Correlation (DIC) is a powerful tool used to evaluate displacements and deformations in a non-intrusive manner. By comparing two images, one of the undeformed reference state of a specimen and another of the deformed target state, the relative displacement between those two states is determined. DIC is well known and often used for post-processing analysis of in-plane displacements and deformation of specimen. Increasing the analysis speed to enable real-time DIC analysis will be beneficial and extend the field of use of this technique. Here we tested several combinations of the most common DIC methods in combination with different parallelization approaches in MATLAB and evaluated their performance to determine whether real-time analysis is possible with these methods. To reflect improvements in computing technology different hardware settings were also analysed. We found that implementation problems can reduce the efficiency of a theoretically superior algorithm such that it becomes practically slower than a suboptimal algorithm. The Newton-Raphson algorithm in combination with a modified Particle Swarm algorithm in parallel image computation was found to be most effective. This is contrary to theory, suggesting that the inverse-compositional Gauss-Newton algorithm is superior. As expected, the Brute Force Search algorithm is the least effective method. We also found that the correct choice of parallelization tasks is crucial to achieve improvements in computing speed. A poorly chosen parallelisation approach with high parallel overhead leads to inferior performance. Finally, irrespective of the computing mode the correct choice of combinations of integerpixel and sub-pixel search algorithms is decisive for an efficient analysis. Using currently available hardware realtime analysis at high framerates remains an aspiration. Y1 - 2019 SP - 1 EP - 17 ER - TY - CHAP A1 - Thoma, Andreas A1 - Fisher, Alex A1 - Braun, Carsten T1 - Improving the px4 avoid algorithm by bio-inspired flight strategies T2 - DLRK2020 - „Luft- und Raumfahrt – Verantwortung in allen Dimensionen“ Y1 - 2020 N1 - Deutscher Luft- und Raumfahrtkongress 2020, 1. bis 3. September 2020 – Online, „Luft- und Raumfahrt – Verantwortung in allen Dimensionen“ ER -