PRBonn/agribot

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PRBonn/agribot

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The mission of the project is to build an agricultural robot (AgriBot) from scratch with the aim of serving as a data-recording platform in fields. For further information about the design and purpose of the robot, please follow the About the AgriBot Project page

Update

remove tf dependencies and included tf2 similar to costmap2D and ros nav core packages.
makes on Melodic and further

AgriBot - Agricultural Mobile Robot Platform

Youtube video

Project mission

The mission of the project is to build an agricultural robot (AgriBot) from scratch with the aim of serving as a data-recording platform in fields. For further information about the design and purpose of the robot, please follow the About the AgriBot Project page

Getting Started

For easily bringing up the robot and recording data refer to Easy bring up & Record Data which provides step-by-step instructions to run the robot.

Main Sections

Easy Bring up & Record Data : Instructions for running the robot and recording the sensor data to a bagfile.
AgriBot Software : Details about different packages written for the platform like navigation, localization, base controller, etc.
Mechanical Design : Detail about how mechanical structure has been designed and improved during the project time.
Electrical Design : Electrical schematics and descriptions about connections and wiring protocols used in the robot.
Debug: Debug procedures for common problems.

Citation

if you use this project in your recent works please reference to our paper by:

@article{ahmadi2021towards,
  title={Towards Autonomous Crop-Agnostic Visual Navigation in Arable Fields},
  author={Ahmadi, Alireza and Halstead, Michael and McCool, Chris},
  journal={arXiv preprint arXiv:2109.11936},
  year={2021}
}

@inproceedings{ahmadi2020visual,
  title={Visual servoing-based navigation for monitoring row-crop fields},
  author={Ahmadi, Alireza and Nardi, Lorenzo and Chebrolu, Nived and Stachniss, Cyrill},
  booktitle={2020 IEEE International Conference on Robotics and Automation (ICRA)},
  pages={4920--4926},
  year={2020},
  organization={IEEE}
}

Maintenance

This repository is maintained by Alireza Ahmadi. In case of any problems, please don't hesitate to contact me.

[email protected]

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lidar-bonnetal

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semantic_suma

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semantic-kitti-api

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OverlapNet

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LiDAR-MOS

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vdbfusion

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SHINE_mapping

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bonnet

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range-mcl

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overlap_localization

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rangenet_lib

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refusion

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bonnetal

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4DMOS

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MapClosures

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LiDiff

[CVPR'24] Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion

visual-crop-row-navigation

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pole-localization

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online_place_recognition

Graph-based image sequences matching for the visual place recognition in changing environments.

LocNDF

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4dNDF

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make_it_dense

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point-cloud-prediction

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ir-mcl

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MutiverseOdometry

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vpr_relocalization

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TARL

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lidar-visualizer

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deep-point-map-compression

segcontrast

auto-mos

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3DUIS

lidar_transfer

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descriptor-dr

[ICRA 2023] Learning-Based Dimensionality Reduction for Computing Compact and Effective Local Feature Descriptors

hsmcl

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ContMAV

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extrinsic_calibration

Motion Based Multi-Sensor Extrinsic Calibration

vdbfusion_ros

ROS1 Wrapper for VDBFusion https://github.com/PRBonn/vdbfusion

DCPCR

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HortiMapping

🫑 Panoptic Mapping with Fruit Completion and Pose Estimation for Horticultural Robots (IROS' 23)

fast_change_detection

Fast Image-Based Geometric Change Detection Given a 3D Model

contrastive_association

Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans

retriever

Point Cloud-based Place Recognition in Compressed Map

4d_plant_registration

tmcl

Text Guided MCL

dynamic-point-removal

Static Map Generation from 3D LiDAR Point Clouds Exploiting Ground Segmentation

MaskPLS

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manifold_python

Python bindings for https://github.com/hjwdzh/Manifold

PS-res-excite

kppr

KPPR: Exploiting Momentum Contrast for Point Cloud-Based Place Recognition

goPro-meta

App to sample images from goPro Hero 5 video and syncronize sensor frames to them. Output is yaml file and extracted images.

geometrical_stem_detection

Code for fast and accurate geometrical plant stem detection

PartiallyObservedInverseGames.jl

An inverse game solver for inferring objectives from noise-corrupted partial state observations of non-cooperative multi-agent interactions.

pybonirob

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phenobench-baselines

Baselines of the PhenoBench Dataset

voxblox_pybind

Python bindings for the Voxblox library

catkin_tools_fetch

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nuscenes2kitti

StyleGenForLabels

StyleGAN-based generation of labels for crop-weed segmentation

plants_temporal_matcher

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ipb_homework_checker

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leaf_mesher

Precise 3D Reconstruction of Plants from UAV Imagery Combining Bundle Adjustment and Template Matching

HAPT

sigf

Image Matching for Crop Fields Using Similarity Invariant Geometric Feature

DG-CWS

Towards Domain Generalization in Crop and Weed Segmentation for Precision Farming Robots

agri-pretraining

leaf-plant-instance-segmentation

In-Field Phenotyping Based on Crop Leaf and Plant Instance Segmentation

MinkowskiPanoptic

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Unsupervised-Pre-Training-for-3D-Leaf-Instance-Segmentation

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vdb_to_numpy

Tool to convert VDB grids to numpy arrays.

Jupyter Notebook

g2o_catkin

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ipb_workspace

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plant_pcd_segmenter

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cinderella-geometric-animations

Animations of geometric properties relevant to Photogrammetry, Computer Vision and Robotics created with Cinderella