Gesunde Lebensmittel

Aufsätze in referierten Fachzeitschriften [1 Ergebnis]

• Shamshiri, R.; Navas, E.; Dworak, V.; Schütte, T.; Weltzien, C.; Auat Cheein, F. (2024): Internet of robotic things with a local LoRa network for teleoperation of an agricultural mobile robot using a digital shadow. Discover Applied Sciences. (6): p. 414. Online: https://doi.org/10.1007/s42452-024-06106-7

Beiträge zu Sammelwerken [4 Ergebnisse]

• Schütte, T.; Koch, K.; Dworak, V.; Weltzien, C. (2023): LiDAR Assisted Semi-automatic Mapping and Path Planning Approach for Autonomous Mobile Robots in Vineyards and Orchards. In: 80th International Conference on Agricultural Engineering. LAND.TECHNIK AgEng 2023. 80th International Conference on Agricultural Engineering. LAND.TECHNIK AgEng 2023. VDI Verlag GmbH, Düsseldorf, (0083-5560, 978-3-18-092427-4), p. 199-207.
• Shamshiri, R.; Navas, E.; Dworak, V.; Fernández, R.; Schütte, T.; Weltzien, C. (2023): Teleoperation of an Agricultural Mobile Robot inside Berry Orchard using LoRa Connectivity. In: 80th International Conference on Agricultural Engineering. LAND.TECHNIK AgEng 2023. 80th International Conference on Agricultural Engineering. LAND.TECHNIK AgEng 2023. VDI Verlag GmbH, Düsseldorf, (0083-5560, 978-3-18-092427-4), p. 191-197.
• Schütte, T.; Dworak, V.; Weltzien, C. (2022): Deriving precise orchard maps for unmanned ground vehicles from UAV images. In: Gandorfer, M.; Hoffmann, C.; El Benni, N.; Cockburn, M.; Anken, T.; Floto, H.(eds.): Informatik in der Land-, Forst- und Ernährungswirtschaft. Fokus: Künstliche Intelligenz in der Agrar- und Ernährungswirtschaft. Referate der 42. GIL-Jahrestagung. 42. GIL-Jahrestagung - Was bedeutet Künstliche Intelligenz für die Agrar- und Ernährungswirtschaft?. Gesellschaft für Informatik, Bonn, (1617-5468/978-3-88579-711-1), p. 271-276. Online: https://gil-net.de/wp-content/uploads/2022/02/GIL-Tagungsband2022.pdf
• Shamshiri, R.; Weltzien, C.; Schütte, T. (2022): Multi-Sensor Data Fusion with Fuzzy Knowledge-based Controller for Collision Avoidance of a Mobile Robot. In: VDI Wissensforum(eds.): Land.Technik 2022. The forum for Agricultural Engineering Innovations. 79th Internationals Conference on Agricultural Engineering Land.Technik. VDI Verlag GmbH, Düsseldorf, (0083-5560/978-3-18-092395-6), p. 349-358.

Vorträge und Poster [7 Ergebnisse]

• Schütte, T.; Koch, K.; Dworak, V.; Weltzien, C. (2024): Safe and robust: 3D mapping for soft collision prediction of autonomous mobile robots in orchards.
• Shamshiri, R.; Navas Merlo, E.; Dworak, V.; Schütte, T.; Weltzien, C. (2023): Teleoperation of an Agricultural Mobile Robot inside Berry Orchard using LoRaWAN Sensors.
• Schütte, T. (2023): LiDAR Assisted Semi-automatic Mapping and Path Planning Approach for Autonomous Mobile Robots in Vineyards and Orchards.
• Schütte, T.; Dworak, V.; Weltzien, C. (2022): Deriving precise orchard maps for unmanned ground vehicles from UAV images.
• Shamshiri, R.; Weltzien, C.; Schütte, T. (2022): Multi-Sensor Data Fusion with Fuzzy Knowledge-based Controller for Collision Avoidance of a Mobile Robot.
• Käthner, J.; Schütte, T. (2021): SunBot: Emission-free berry production in Brandenburg.
• Schütte, T. (2021): Digitized Agriculture - Chances and Challenges for IoT and CLEC Technology.