Vinobot and Vinoculer: Two Robotic Platforms for High-Throughput Field Phenotyping
| Autor: | Felix B. Fritschi, Suhas Kadam, Guilherme N. DeSouza, Ali Shafiekhani |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0106 biological sciences
vision Engineering Real-time computing Detailed data lcsh:Chemical technology 01 natural sciences Biochemistry Article Field (computer science) Analytical Chemistry Observation tower lcsh:TP1-1185 Computer vision 3D reconstruction Electrical and Electronic Engineering Architecture Instrumentation Throughput (business) robotics Data collection business.industry 3d image processing field phenotyping 04 agricultural and veterinary sciences Plant phenotyping Atomic and Molecular Physics and Optics mobile robotics 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Artificial intelligence business 010606 plant biology & botany |
| Zdroj: | Sensors (Basel, Switzerland) Sensors, Vol 17, Iss 1, p 214 (2017) Sensors Volume 17 Issue 1 |
| ISSN: | 1424-8220 |
| DOI: | 10.3390/s17010214 |
| Popis: | In this paper, a new robotic architecture for plant phenotyping is being introduced. The architecture consists of two robotic platforms: an autonomous ground vehicle (Vinobot) and a mobile observation tower (Vinoculer). The ground vehicle collects data from individual plants, while the observation tower oversees an entire field, identifying specific plants for further inspection by the Vinobot. The advantage of this architecture is threefold: first, it allows the system to inspect large areas of a field at any time, during the day and night, while identifying specific regions affected by biotic and/or abiotic stresses second, it provides high-throughput plant phenotyping in the field by either comprehensive or selective acquisition of accurate and detailed data from groups or individual plants and third, it eliminates the need for expensive and cumbersome aerial vehicles or similarly expensive and confined field platforms. As the preliminary results from our algorithms for data collection and 3D image processing, as well as the data analysis and comparison with phenotype data collected by hand demonstrate, the proposed architecture is cost effective, reliable, versatile, and extendable. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|