840: Delicate Viticultural Robotics — with Jon Krohn (@JonKrohnLearns)

Robotic Challenges

The development of robotics for harvesting delicate wine grapes presents unique challenges. Jon Krohn explains that these grapes have traditionally resisted mechanical intervention due to their sensitivity, making it difficult to harvest them without damage. A collaborative project between Queen Mary University of London and Extend Robotics aims to address these challenges by integrating advanced sensing systems and precise robotic control 1. The system employs spectroscopic analysis to assess grape ripeness and pressure-sensitive mechanical manipulation for harvesting.

The innovative news, now announced a few weeks ago, is a collaborative project between Queen Mary University of London and a startup called Extend Robotics that are together working to overcome these grape harvesting challenges through an integration of advanced sensing systems and precise robotic control.

--- Jon Krohn

Machine learning models are used to filter spectral data, isolating key wavelength patterns associated with grape ripeness while disregarding irrelevant environmental data 1.

   

Technological Innovations

Innovative technologies are transforming viticulture, particularly through the use of spectroscopic sensors and VR control. Jon Krohn highlights the use of transmitted light analysis to determine grape composition, a technique that faces challenges in real-world conditions but is crucial for assessing sugar content, a key indicator of ripeness 1. The project employs a VR interface for human-in-the-loop control, enabling precise operation and generating training data for future autonomous systems.

The current VR controlled system provides a practical solution to this problem in the case of this viticultural application, by enabling human operators to generate high quality training data through remote operation.

--- Jon Krohn

This approach allows for continuous operation by leveraging global time zones, with operators in Australia controlling robots during UK nighttime hours, thus addressing labor shortages and maximizing equipment use 2.