Containerized Vertical Farming Using Cobots

TL;DR

This paper demonstrates how cobots can be used to automate transplantation and harvesting in containerized vertical farming using a single demonstration and RGBD imaging, reducing the need for task-specific programming.

Contribution

It introduces a method for learning task constraints from a single demonstration to automate farming operations with cobots in confined container environments.

Findings

Feasibility of using RGBD cameras for task execution

Successful automation of transplantation and harvesting tasks

Single demonstration suffices for task generalization

Abstract

Containerized vertical farming is a type of vertical farming practice using hydroponics in which plants are grown in vertical layers within a mobile shipping container. Space limitations within shipping containers make the automation of different farming operations challenging. In this paper, we explore the use of cobots (i.e., collaborative robots) to automate two key farming operations, namely, the transplantation of saplings and the harvesting of grown plants. Our method uses a single demonstration from a farmer to extract the motion constraints associated with the tasks, namely, transplanting and harvesting, and can then generalize to different instances of the same task. For transplantation, the motion constraint arises during insertion of the sapling within the growing tube, whereas for harvesting, it arises during extraction from the growing tube. We present experimental results to show that using RGBD camera images (obtained from an eye-in-hand configuration) and one demonstration for each task, it is feasible to perform transplantation of saplings and harvesting of leafy greens using a cobot, without task-specific programming.