To increase understanding of the interaction between phenotype and genotype x environment to improve crop performance, large amounts of phenotypic data are needed. Studying plants of a given strain under multiple environments can greatly help to reveal their interactions. To collect the labor-intensive data required to perform experiments in this area, a Mecanum-wheeled, magnetic-tape-following indoor rover has been developed to accurately and autonomously move between and inside growth chambers. Integration of the motor controllers, a robot arm, and a Microsoft Kinect (v2) 3D sensor was achieved in a customized C++ program. Detecting and segmenting plants in a multi-plant environment is a challenging task, which can be aided by integration of depth data into these algorithms. Image-processing functions were implemented to filter the depth image to minimize noise and remove undesired surfaces, reducing the memory requirement and allowing the plant to be reconstructed at a higher resolution in real-time. Three-dimensional meshes representing plants inside the chamber were reconstructed using the Kinect SDK’s KinectFusion. After transforming user-selected points in camera coordinates to robot-arm coordinates, the robot arm is used in conjunction with the rover to probe desired leaves, simulating the future use of sensors such as a fluorimeter and Raman spectrometer. This paper reports the system architecture and some preliminary results of the system.
Available at: http://works.bepress.com/lie_tang/42/
This article is published as Shah, Dylan, Lie Tang, Jingyao Gai, and Rajesh Putta-Venkata. "Development of a mobile robotic phenotyping system for growth chamber-based studies of genotype x environment interactions." IFAC-PapersOnLine 49, no. 16 (2016): 248-253. DOI: 10.1016/j.ifacol.2016.10.046. Posted with permission.