Background
Pollination is a crucial ecosystem service vital for preserving plant communities, both wild and agricultural. With pollinator species populations declining, plant reproduction suffers, leading to a loss of biodiversity and impacting dependent ecosystems. Our project seeks to investigate the environmental, technological and ethical implications of using innovative robotics technology to address these challenges. Our cross-disciplinary team comprises Ecologists, Biologists, and Roboticists from the PROTEAS group at the Bristol Robotics Laboratory, along with collaborators from ecology and environmental groups. We aim to quantifiably improve pollination efficiency and contribute to the preservation of vital ecosystems, while upholding ethical and sustainable practices.
Project Motivation
We aim to design and build a robotic pollinator for use in areas where pollinators have become locally extinct or where their use is considered unsustainable.
The ever-growing population is putting more and more pressure on agricultural systems, and to keep up with this growing demand, increasingly vast areas of land are being deforested to create pasture land or turned into monoculture plantations. This, more often than not, leads to huge downturns in biodiversity, often resulting in the local or complete extinction of pollinators [1,2].
This project hopes to create a solution to these issues by providing a robotic alternative for use in agriculture where natural pollinators are either missing or suffering. Ultimately, we hope to help kickstart rewilding by robotically introducing and pollinating wild fruit trees in deforested areas, in turn, encouraging the return of seed spreading frugivores [3].
Find out more here:
Project Aims:
Design, build and test a robotic pollinator for use in environments where natural pollinators are locally extinct, or where the use of natural pollinators is practiced unsustainably, such as in Californian almond groves or Chinese pear orchards.
Project Objectives:
Design pollination equipment suitable for use with an existing micro-UAV platform
Design a machine vision algorithm to allow for flower identification of flowers in the family Rosacaea
Design a flight controller to allow for micro-UAV and pollination device control
Integrate machine vision and flight controller to enable autonomous pollination of flowers by the Pollibot.
Project Progress:
First flights have taken place using a Crazyflie 2.0 MAV!
Funding:
This work is supported by a seedcorn fund from the Cabot Institute