@inproceedings{6790,
  abstract     = {Manual waste monitoring is a labor-intensive process that can lead to unnecessary trips and overflowing waste bins due to fixed inspection schedules. Existing automated systems rely on static sensors installed inside each bin, which are difficult to scale and have not yet gained wider acceptance. Micro aerial vehicles (MAVs) can address this problem by carrying the necessary sensors to different locations as needed. This paper presents an MAV-based solution for automated waste bin monitoring. RGB images captured by the MAV are processed by a CNN to estimate fill levels without the need for in-bin sensors. The CNN is trained on a custom dataset of simulated waste bins and evaluated with respect to dataset performance and in a real application scenario. A mobile application enables operators to configure bin locations and monitor the process in real time. The MAV is controlled by a reinforcement learning policy and autonomously navigates to each bin location. The evaluation demonstrates that the CNN achieves reliable performance on both simulated and real images, and that the integrated system autonomously completes full inspection cycles. Overall, the proposed system offers a scalable and cost-efficient alternative for sustainable waste management.},
  author       = {Kirsch, André and Rexilius, Jan},
  booktitle    = {22nd International Conference on Intelligent Environments (IE)},
  keywords     = {Waste monitoring, Waste level estimation, MAV navigation},
  location     = {Lissabon, Portugal},
  title        = {{Vision-Based Autonomous Waste Bin Fill-Level Monitoring with a Micro Aerial Vehicle}},
  doi          = {10.1109/IE69249.2026.11539031},
  year         = {2026},
}

@inproceedings{5771,
  author       = {Kirsch, André and Rexilius, Jan},
  booktitle    = { Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods },
  editor       = {Castrillon-Santana, Modesto  and De Marsico, Maria and Fred, Ana },
  isbn         = { 978-989-758-730-6},
  issn         = {2184-4313},
  keywords     = {Tracking, Robot, Drone, MAV, External, Time-of-Flight, LiDAR},
  location     = {Porto},
  publisher    = {Science and Technology Publications},
  title        = {{ An Easy-to-Use System for Tracking Robotic Platforms Using Time-of-Flight Sensors in Lab Environments}},
  doi          = {10.5220/0013110500003905},
  year         = {2025},
}

@inproceedings{5281,
  author       = {Riechmann-Thom, Malte and Kirsch, André and König, Matthias and Rexilius, Jan},
  booktitle    = {2024 IEEE International Conference on Robotics and Automation (ICRA)},
  location     = {Yokohama},
  title        = {{Virtual Borders in 3D: Defining a Drone’s Movement Space Using Augmented Reality}},
  doi          = {10.1109/ICRA57147.2024.10610259},
  year         = {2024},
}

@misc{5269,
  author       = {Kirsch, André and Rexilius, Jan},
  publisher    = {Hochschule Bielefeld},
  title        = {{Robotic Platform Tracking}},
  year         = {2024},
}

@inproceedings{3655,
  author       = {Kirsch, André and Matutat, André and Reinsch, Malte and George, Birgit Christina and Gips, Carsten},
  booktitle    = {Proceedings of the Sixth Workshop "Automatische Bewertung von Programmieraufgaben" (ABP 2023)},
  editor       = {Greubel, André and Strickroth, Sven and Striewe, Michael},
  keywords     = {Autograding, Automatisiertes Feedback, CI/CD-Pipeline},
  location     = {München},
  publisher    = {Gesellschaft für Informatik e.V.},
  title        = {{Deploy-to-Grading: Automatische Bewertung von Programmieraufgaben mit CI/CD-Pipelines}},
  doi          = {10.18420/ABP2023-11},
  year         = {2023},
}

@inproceedings{3656,
  author       = {Kirsch, André and Riechmann, Malte and König, Matthias},
  booktitle    = {2023 European Conference on Mobile Robots (ECMR)},
  location     = {Coimbra, Portugal},
  publisher    = {IEEE},
  title        = {{Assisted Localization of MAVs for Navigation in Indoor Environments Using Fiducial Markers}},
  doi          = {10.1109/ECMR59166.2023.10256424},
  year         = {2023},
}

@misc{6306,
  author       = {Kirsch, André and Riechmann-Thom, Malte and König, Matthias},
  publisher    = {Hochschule Bielefeld},
  title        = {{Assisted Localization of MAVs for Navigation in Indoor Environments Using Fiducial Markers}},
  year         = {2023},
}

@misc{6350,
  author       = {Kirsch, André and Riechmann-Thom, Malte and König, Matthias},
  title        = {{System und Verfahren zur Eingabe von virtuellen Objekten in drei Dimensionen mittels Augmented Reality zum Ermitteln des Bewegungsraums für Roboter}},
  year         = {2023},
}

@inproceedings{4295,
  author       = {Matutat, André and Reinsch, Malte and Kirsch, André and George, Birgit Christina and Gips, Carsten},
  booktitle    = {StartPlay 2023 : Proceedings of the 2nd Interdisciplinary Conference on Gamification and Innovation},
  location     = {Bergische Universität Wuppertal},
  publisher    = {Bergische Universität Wuppertal},
  title        = {{Learning by Questing}},
  year         = {2023},
}

@inproceedings{4307,
  author       = {Riechmann, Malte and Kirsch, André and König, Matthias},
  booktitle    = {2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)},
  location     = {Sydney, Australia},
  pages        = {561--566},
  publisher    = {IEEE},
  title        = {{Augmented Reality for Interactive Path Planning in 3D}},
  doi          = {10.1109/ISMAR-Adjunct60411.2023.00119},
  year         = {2023},
}

@inproceedings{1966,
  author       = {Kirsch, André and Günter, Andrei and König, Matthias},
  booktitle    = {12th International Conference on Pattern Recognition Systems},
  keywords     = {alignability prediction, point cloud registration, overlap metric, descriptors},
  location     = {Saint-Étienne},
  publisher    = {IEEE},
  title        = {{Predicting Alignability of Point Cloud Pairs for Point Cloud Registration Using Features}},
  doi          = {10.1109/ICPRS54038.2022.9854071},
  year         = {2022},
}

@misc{5270,
  author       = {Kirsch, André and Günter, Andrei and König, Matthias},
  publisher    = {Hochschule Bielefeld},
  title        = {{Predicting Alignability of Point Cloud Pairs for Point Cloud Registration Using Features}},
  year         = {2022},
}