mlsanityData to 14 Oct 2026

Advanced techniques and applications of LiDAR Place Recognition in Agricultural Environments: A Comprehensive Survey

arXiv 2601.22198 ↗First posted 29 Jan 2026cs.RO cs.AI cs.ETcited by 1

Not on the map. Why?

Abstract (arXiv)

An optimal solution to the localization problem is essential for developing autonomous robotic systems. Apart from autonomous vehicles, precision agriculture is one of the elds that can bene t most from these systems. Although LiDAR place recognition is a widely used technique in recent years to achieve accurate localization, it is mostly used in urban settings. However, the lack of distinctive features and the unstructured nature of agricultural environments make place recognition challenging. This work presents a comprehensive review of state-of-the-art the latest deep learning applications for agricultural environments and LPR techniques. We focus on the challenges that arise in these environments. We analyze the existing approaches, datasets, and metrics used to evaluate LPR system performance and discuss the limitations and future directions of research in this eld. This is the rst survey that focuses on LiDAR based localization in agricultural settings, with the aim of providing a thorough understanding and fostering further research in this specialized domain.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 60 of its 190 references that are in the map. First posted on arXiv 29 Jan 2026.

Builds on

60 of 190 references.

References · 60

  1. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  2. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,845
  3. 2015NetVLAD: CNN architecture for weakly supervised place recognitioncited by 941
  4. 2016ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Camerascited by 806
  5. 2022Matryoshka Representation Learningcited by 282
  6. 2018PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognitioncited by 198
  7. 2023AnyLoc: Towards Universal Visual Place Recognitioncited by 163
  8. 2020RELLIS-3D Dataset: Data, Benchmarks and Analysiscited by 119
  9. 2020MinkLoc3D: Point Cloud Based Large-Scale Place Recognitioncited by 115
  10. 2021Where is your place, Visual Place Recognition?cited by 82
  11. 2021Scan Context++: Structural Place Recognition Robust to Rotation and Lateral Variations in Urban Environmentscited by 72
  12. 2017Real-time Semantic Segmentation of Crop and Weed for Precision Agriculture Robots Leveraging Background Knowledge in CNNscited by 55
38 more
  1. 2022Improving Point Cloud Based Place Recognition with Ranking-based Loss and Large Batch Trainingcited by 45
  2. 2019SegMap: Segment-based mapping and localization using data-driven descriptorscited by 42
  3. 2023Loss Functions and Metrics in Deep Learningcited by 42
  4. 2021MinkLoc++: Lidar and Monocular Image Fusion for Place Recognitioncited by 41
  5. 2019MinneApple: A Benchmark Dataset for Apple Detection and Segmentationcited by 39
  6. 2023BEVPlace: Learning LiDAR-based Place Recognition using Bird's Eye View Imagescited by 39
  7. 2016Deep Fruit Detection in Orchardscited by 38
  8. 2020Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Poolingcited by 38
  9. 2020Intensity Scan Context: Coding Intensity and Geometry Relations for Loop Closure Detectioncited by 37
  10. 2021AdaFusion: Visual-LiDAR Fusion with Adaptive Weights for Place Recognitioncited by 36
  11. 2022ORFD: A Dataset and Benchmark for Off-Road Freespace Detectioncited by 33
  12. 2023Visual Place Recognition: A Tutorialcited by 31
  13. 2019Crop Yield Prediction Using Deep Neural Networkscited by 29
  14. 2024General Place Recognition Survey: Towards Real-World Autonomycited by 23
  15. 2022InCloud: Incremental Learning for Point Cloud Place Recognitioncited by 22
  16. 2022CASSPR: Cross Attention Single Scan Place Recognitioncited by 22
  17. 2023LiDAR-Based Place Recognition For Autonomous Driving: A Surveycited by 21
  18. 2020CORAL: Colored structural representation for bi-modal place recognitioncited by 18
  19. 2018Robust Fruit Counting: Combining Deep Learning, Tracking, and Structure from Motioncited by 13
  20. 2021MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions, spherical coordinates, and intensitycited by 12
  21. 2022Position-Agnostic Autonomous Navigation in Vineyards with Deep Reinforcement Learningcited by 11
  22. 2021Bumblebee: A Path Towards Fully Autonomous Robotic Vine Pruningcited by 10
  23. 2022CGiS-Net: Aggregating Colour, Geometry and Implicit Semantic Features for Indoor Place Recognitioncited by 9
  24. 2020Local Motion Planner for Autonomous Navigation in Vineyards with a RGB-D Camera-Based Algorithm and Deep Learning Synergycited by 8
  25. 2024MambaPlace:Text-to-Point-Cloud Cross-Modal Place Recognition with Attention Mamba Mechanismscited by 7
  26. 2024GSPR: Multimodal Place Recognition Using 3D Gaussian Splatting for Autonomous Drivingcited by 7
  27. 2020SLAM in the Field: An Evaluation of Monocular Mapping and Localization on Challenging Dynamic Agricultural Environmentcited by 6
  28. 2021Multispectral Vineyard Segmentation: A Deep Learning approachcited by 6
  29. 2023Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farmscited by 6
  30. 2024MinkUNeXt: Point Cloud-based Large-scale Place Recognition using 3D Sparse Convolutionscited by 6
  31. 2025Keypoint Semantic Integration for Improved Feature Matching in Outdoor Agricultural Environmentscited by 5
  32. 2022Waypoint Generation in Row-based Crops with Deep Learning and Contrastive Clusteringcited by 4
  33. 2023Vision-based Vineyard Navigation Solution with Automatic Annotationcited by 4
  34. 2023BonnBot-I: A Precise Weed Management and Crop Monitoring Platformcited by 4
  35. 2024The GREENBOT dataset: Multimodal mobile robotic dataset for a typical Mediterranean greenhousecited by 3
  36. 2024PointNetPGAP-SLC: A 3D LiDAR-based Place Recognition Approach with Segment-level Consistency Training for Mobile Robots in Horticulturecited by 3
  37. 2025LRFusionPR: A Polar BEV-Based LiDAR-Radar Fusion Network for Place Recognitioncited by 3
  38. 2025Autonomous Robotic Pruning in Orchards and Vineyards: a Reviewcited by 3

50 most cited of 60 All 60 (JSON)

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Heterogeneous LiDAR Early Fusion and Learned Re-Ranking Strategy for Robust Long-Term Place Recognition in Unstructured Environmentscited by 0