# BonnBot-I Plus: A Bio-diversity Aware Precise Weed Management Robotic Platform

arXiv: https://arxiv.org/abs/2405.09118 · HTML: https://mlsanity.com/paper/2405.09118/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 22 references that are in the map.
- First posted on arXiv 15 May 2024.

## Builds on (most cited first, 3 of 3)

- [Mask R-CNN](https://mlsanity.com/paper/1703.06870/) (2017)
- [Virtual Temporal Samples for Recurrent Neural Networks: applied to semantic segmentation in agriculture](https://mlsanity.com/paper/2106.10118/) (2021)
- [BonnBot-I: A Precise Weed Management and Crop Monitoring Platform](https://mlsanity.com/paper/2307.12588/) (2023)

## Built on by (most cited first, 1 of 1)

- [Advancements in Weed Mapping: A Systematic Review](https://mlsanity.com/paper/2507.01269/) (2025)

## Abstract (arXiv)

In this article, we focus on the critical tasks of plant protection in arable farms, addressing a modern challenge in agriculture: integrating ecological considerations into the operational strategy of precision weeding robots like bbot. This article presents the recent advancements in weed management algorithms and the real-world performance of bbot at the University of Bonn's Klein-Altendorf campus. We present a novel Rolling-view observation model for the BonnBot-Is weed monitoring section which leads to an average absolute weeding performance enhancement of 3.4%. Furthermore, for the first time, we show how precision weeding robots could consider bio-diversity-aware concerns in challenging weeding scenarios. We carried out comprehensive weeding experiments in sugar-beet fields, covering both weed-only and mixed crop-weed situations, and introduced a new dataset compatible with precision weeding. Our real-field experiments revealed that our weeding approach is capable of handling diverse weed distributions, with a minimal loss of only 11.66% attributable to intervention planning and 14.7% to vision system limitations highlighting required improvements of the vision system.