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Collaborative project: Experimental environment for the industrial development of semantic environmental perception - subproject A (AI-TEST-FIELD)
Project
Project code: 28DK101A20
Contract period: 01.01.2021
- 31.10.2024
Budget: 520,372 Euro
Purpose of research: Applied research
Keywords: AI Artificial Intelligence, information-communicationtechnology, resource protection, resource efficiency, precision farming, data management, agricultural engineering, crop production
Autonomous agricultural robots and highly automated agricultural machinery have the potential to offer a solution in the area of tension between efficient and sustainable ecological agriculture. These systems exist as research prototypes but do not make it onto the market. This is largely due to the lack of evidence of the robustness of the perception of the environment under the widely varying boundary conditions of agriculture and the resulting lack of approvals. The TÜV is therefore involved in the project. This is where the AI-TEST FIELD project comes in and is developing a test field that enables the semantic perception of the environment by sensor systems under real year-round weather conditions and field conditions, right up to functional safety (person recognition). Due to the reproducible movement of a sensor carrier on a rail / carrier infrastructure, the robustness of the algorithms for interpreting promising sensor systems with different measurement principles is evaluated and improved.
Section overview
Subjects
- Crop Production
Framework programme
Funding programme
Excutive institution
German Research Center for Artificial Intelligence GmbH (DFKI)
Funding institution
Project management agencies
Associated projects: AI-TEST-FIELD
- Collaborative project: Experimental environment for the industrial development of semantic environmental perception - subproject B
- Collaborative project: Experimental environment for the industrial development of semantic environmental perception - subproject C
- Collaborative project: Experimental environment for the industrial development of semantic environmental perception - subproject D
