Provision of general purpose datasets via multisensored aerial robot
National Institute for Research in Digital Science and Technology - INRIA
Location
France
At user's premises
Arable farming
Food processing
Greenhouse
Horticulture
Tree Crops
Viticulture
General-purpose datasets serve two primary objectives:
- Evaluating mobility algorithms;
- Developing and assessing general-purpose AI applications.
In the context of mobility algorithms, this pertains to classical robotics tasks such as mapping, localization, SLAM (Simultaneous Localization and Mapping), and navigation.
Meanwhile, general-purpose AI applications focus on advancing algorithms and feeding decision support systems (DSS) for tasks like but not limited to weed detection, health monitoring, growth and maturity assessment, and yield estimation in areas like arable farming, horticulture, food processing, forestry, and tree management.
A significant challenge in developing AI solutions for agricultural robotics lies in the dynamic nature of agricultural environments, which fluctuate with different seasons and weather conditions.
To address this, acquiring consistent and periodic data is essential for monitoring these changes effectively. This real-time data collection, often facilitated by aerial robots, is crucial for developing efficient algorithms and AI solutions. Such datasets can support the development of sensor-specific techniques or be leveraged to create multisensory algorithms, enabling more accurate and adaptable systems for agricultural applications.
AI model training
Collection of test data
Data analysis
Data augmentation
Desk assessment
Performance evaluation
Provision of datasets
Test design
Test setup
Text execution