Development of a Robotic Crop Phenotyping Testbed for Sustainable Agriculture

Ali Imran, Muhammad Owais Tahir, Abubakr Muhammad, Muhammad Shabbir Hasan

Keywords: robotics, phenotyping, agricultural dataset, lidar, multispectral

TL;DR: Development of a robotic platform to collect a comprehensive dataset for digital phenotyping and precision agriculture

Abstract: To meet the food demands of increasing global population, it is essential to make advancements in the field of genomics and plant phenotyping to explore novel traits in plants. This would require developing automated phenotyping methods which are efficient, and less prone to human error and bias. This paper presents the work on development of a robotic platform, equipped with a diverse set of sensors, enabling it to gather a rich data set of essential parameters required for digital phenotyping. The goal of the project is to aid small scale farmers, with limited resources, to adopt sustainable agricultural practices and optimize the yield of their products.