Agroecology Lab 2023

Posted on by niblet

Developing an R&D field robot

A R&D platform based on the Twisted Fields Acorn rover. Using the existing electronics and software stack  which features:

Proposed BOM for  R&D field robot

Project v1.0 – Mechanical weeding between crop rows

The project is to test and validate the Visual servoing code we have ported to ROS2 and integrate it into Twisted fields code. Using visual servoing as the local planner & Twisted fields as the global planner / GPS waypoint follower.

The robot will pull simple mechanical hoe between the crop rows

Project v2.0 – Automated charging

Automatic charging. Development of Navigation and mechanical components to enable the robot to return to a charging dock

Project v3.0 – Delta weeding

This will enhance the weeding capability using a AI driven Delta robot to enable more accurate weeding

Project v4.0 – Harvesting

Using Quick cut greens harvester attachment

Business concept

Lease open hardware robots to farmers.

Background

1) I am a working horticultural business and can provide a site near Bristol for robotic experiments in weeding, navigation etc. Agroecology lab will trade as https://nibleyleaves.co.uk/ this year. We sell mixed salad to Bristol restaurants.

2) I have some expertise in LoRa mesh networking and could provide a long-range comms system for Telemetry, RTK data based on the established https://github.com/meshtastic/ project

3) I have considerable experience in wireless mesh networking and could provide field-scale multi-radio mesh connectivity, https://libremesh.org/howitworks.html

4) I am collaborating on https://github.com/Twisted-Fields on the Acorn rover and have a particular interest in developing a more accessible scaled-down version of the rover. This could be used as an open-hardware experimental platform for RTK sensor fusion/ Visual servoing.

5) I have got this ported this project to ROS2 https://github.com/Agroecology-Lab/visual-multi-crop-row-navigation/tree/ROS2 and would be interested in developing it further as an in-crop visual-servoing navigation strategy.