NeXaTauto - Holistic conception, field-based practical testing and validation of autonomous work processes in crop production

The Kalverkamp company, with the support of the Working Group for Optimization and Optimal Control of the Center for Technomathematics and the Osnabrück University of Applied Sciences, is developing the novel, electrically driven, multifunctional agricultural vehicle NeXaT for autonomous agriculture and the elimination of ecological and economic weak points of today's tractor combinations.
Equipped with four individually controllable tape drives, the NeXaT vehicle moves with a width of 18 m on a contact surface with the field that is only 60 cm wide. Compared to conventional farming methods, this allows damage caused by soil compaction to be minimized as far as possible.
The aim of the NeXaTauto project is to make this novel concept autonomously usable in the field using so-called digital twins and techniques of non-linear optimization and artificial intelligence, and to gain new insights through practical tests under real conditions.

The project is supported by funds of the German Government’s Special Purpose Fund held at Landwirtschaftliche Rentenbank.

Publications

1. M. Höffmann, S. Patel, C. Büskens.
   Optimal guidance track generation for precision agriculture: A review of coverage path planning techniques.
   Journal of Field Robotics, Wiley Online Library, , Wiley, 2024.

   DOI: 10.1002/rob.22286

2. M. Höffmann, S. Patel, C. Büskens.
   Optimal Coverage Path Planning for Agricultural Vehicles with Curvature Constraints.
   MDPI Open Access Journals Agriculture, 13(11), 2023.

   DOI: 10.3390/agriculture13112112

3. R. Simonelli, M. Höffmann, S. Patel, C. Büskens.
   Optimal Path Tracking: Benchmarking an NMPC for a Wide-Span Autonomous Agricultural Machine.
   European Control Conference (ECC) 2023, Bucharest, Romania.
   

   online at: https://ieeexplore.ieee.org/document/10178268

4. D. Stronzek-Pfeifer, F. M. Chemmadan, S. Patel, C. Büskens.
   LiDAR-based object detection for agricultural robots.
   GAMM 93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics, 30.05.-02.06.2023, , Dresden.
   Proceedings in Applied Mathematics & Mechanics, Wiley, 2023.

   online at: https://doi.org/10.1002/pamm.202300128

5. R. Simonelli, C. Büskens.
   Modeling and parameter identification for agricultural machines .
   GAMM 93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics, 30.05.-02.06.2023, , Dresden.
   Proceedings in Applied Mathematics & Mechanics, Wiley, 2023.

   DOI: 10.1002/pamm.202300204
   online at: https://onlinelibrary.wiley.com/doi/full/10.1002/pamm.202300204

6. M. Höffmann, S. Patel, C. Büskens.
   Weight-Optimized NURBS Curves: Headland Paths for Nonholonomic Field Robots.
   2022 8th International Conference on Automation, Robotics and Applications (ICARA), 18.02.2022 - 20.02.2022.
   Proceedings of the 8th International Conference on Automation, Robotics and Applications, pp. 81-85, 2022.

   DOI: 10.1109/ICARA55094.2022.9738525
   online at: https://ieeexplore.ieee.org/document/9738525

7. M. Höffmann, J. Clemens, D. Stronzek-Pfeifer, R. Simonelli, A. Serov, S. Schettino, M. Runge, K. Schill, C. Büskens.
   Coverage Path Planning and Precise Localization for Autonomous Lawn Mowers.
   IEEE 6th International Conference on Robotic Computing (IRC), 05.12.-07.12.2022.
   Proceedings of International Conference on Robotic Computing, pp. 238-242, 2022.

   DOI: 10.1109/IRC55401.2022.00046
   online at: https://ieeexplore.ieee.org/document/10023754