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Grzegorz Cielniak

17 accepted papers

2026

Navigating Narrow Spaces: A Comprehensive Framework for Agricultural Robots

Geesara Kulathunga, Abdurrahman Yilmaz, Zhuoling Huang, Ibrahim Hroob, Leonardo Guevara, Jaspreet Singh +2
ICRA 2026poster

Navigating within narrow spaces is a fundamental challenge in robotics, requiring precise localisation, localisation error recovery, dynamic path planning, and adaptive control for effective manoeuvring. This paper presents a modular and perception-driven navigation framework designed for constraine…

Cited by 0Source ↗Scholar ↗
2025

Navigating Narrow Spaces: A Comprehensive Framework for Agricultural Robots

Geesara Kulathunga, Abdurrahman Yilmaz, Zhuoling Huang, Ibrahim Hroob, Jaspreet Singh, Leonardo Guevara +2
RA-L 2025

Navigating within narrow spaces is a fundamental challenge in robotics, requiring precise localisation, localisation error recovery, dynamic path planning, and adaptive control for effective manoeuvring. This paper presents a modular and perception-driven navigation framework designed for constraine

Cited by 2Source ↗Scholar ↗
2023

Statistical shape representations for temporal registration of plant components in 3D

Karoline Heiwolt, Cengiz Öztireli, Grzegorz Cielniak
ICRA 2023poster

Plants are dynamic organisms and understanding temporal variations in vegetation is an essential problem for robots in the wild. However, associating repeated 3D scans of plants across time is challenging. A key step in this process is re-identifying and tracking the same individual plant components…

Cited by 5Source ↗Scholar ↗
2022

Elevation State-Space: Surfel-Based Navigation in Uneven Environments for Mobile Robots

Fetullah Atas, Grzegorz Cielniak, Lars Grimstad
IROS 2022poster

This paper introduces a new method for robot motion planning and navigation in uneven environments through a surfel representation of underlying point clouds. The proposed method addresses the shortcomings of state-of-the-art navigation methods by incorporating both kinematic and physical constraint…

Cited by 14Source ↗code ↗Scholar ↗
2022

Self-supervised Representation Learning for Reliable Robotic Monitoring of Fruit Anomalies

Taeyeong Choi, Owen Would, Adrian Salazar-Gomez, Grzegorz Cielniak
ICRA 2022poster

Data augmentation can be a simple yet powerful tool for autonomous robots to fully utilise available data for self-supervised identification of atypical scenes or objects. State-of-the-art augmentation methods arbitrarily embed “structural” peculiarity on typical images so that classifying these art…

Cited by 18Source ↗code ↗Scholar ↗
2021

Efficient and Robust Orientation Estimation of Strawberries for Fruit Picking Applications

Nikolaus Wagner, Raymond Kirk, Marc Hanheide, Grzegorz Cielniak
ICRA 2021poster

Recent developments in agriculture have high-lighted the potential of as well as the need for the use of robotics. Various processes in this field can benefit from the proper use of state of the art technology [1], in terms of efficiency as well as quality. One of these areas is the harvesting of ri…

Cited by 25Source ↗Scholar ↗
2021

Integration of a Human-aware Risk-based Braking System into an Open-Field Mobile Robot

José C. Mayoral, Lars Grimstad, Pål J. From, Grzegorz Cielniak
ICRA 2021poster

Safety integration components for robotic applications are a mandatory feature for any autonomous mobile application, including human avoidance behaviors. This paper proposes a novel parametrizable scene risk evaluator for open-field applications that use humans motion predictions and pre-defined ha…

Cited by 7Source ↗Scholar ↗
2020

Incorporating Spatial Constraints into a Bayesian Tracking Framework for Improved Localisation in Agricultural Environments

Muhammad W. Khan, Gautham P. Das, Marc Hanheide, Grzegorz Cielniak
IROS 2020poster

Global navigation satellite system (GNSS) has been considered as a panacea for positioning and tracking since the last decade. However, it suffers from severe limitations in terms of accuracy, particularly in highly cluttered and indoor environments. Though real-time kinematics (RTK) supported GNSS…

Cited by 15Source ↗Scholar ↗
2020

Real-time detection of broccoli crops in 3D point clouds for autonomous robotic harvesting

Hector A. Montes, Justin Le Louedec, Grzegorz Cielniak, Tom Duckett
IROS 2020poster

Real-time 3D perception of the environment is crucial for the adoption and deployment of reliable autonomous harvesting robots in agriculture. Using data collected with RGB-D cameras under farm field conditions, we present two methods for processing 3D data that reliably detect mature broccoli heads…

Cited by 22Source ↗Scholar ↗
2019

Go with the Flow: Exploration and Mapping of Pedestrian Flow Patterns from Partial Observations

Sergi Molina, Grzegorz Cielniak, Tom Duckett
ICRA 2019poster

Understanding how people are likely to behave in an environment is a key requirement for efficient and safe robot navigation. However, mobile platforms are subject to spatial and temporal constraints, meaning that only partial observations of human activities are typically available to a robot, whil…

Cited by 22Source ↗Scholar ↗
2019

Semantically Assisted Loop Closure in SLAM Using NDT Histograms

Anestis Zaganidis, Alexandros Zerntev, Tom Duckett, Grzegorz Cielniak
IROS 2019poster

Precise knowledge of pose is of great importance for reliable operation of mobile robots in outdoor environments. Simultaneous localization and mapping (SLAM) is the online construction of a map during exploration of an environment. One of the components of SLAM is loop closure detection, identifyin…

Cited by 50Source ↗Scholar ↗
2019

Warped Hypertime Representations for Long-Term Autonomy of Mobile Robots

Tomás Krajník, Tomás Vintr, Sergi Molina Mellado, Jaime Pulido Fentanes, Grzegorz Cielniak, Óscar Martínez Mozos +2
RA-L 2019

This letter presents a novel method for introducing time into discrete and continuous spatial representations used in mobile robotics, by modeling long-term, pseudo-periodic variations caused by human activities or natural processes. Unlike previous approaches, the proposed method does not treat tim

Cited by 29Source ↗Scholar ↗
2018

3-D Soil Compaction Mapping Through Kriging-Based Exploration With a Mobile Robot

Jaime Pulido Fentanes, Iain Gould, Tom Duckett, Simon Pearson, Grzegorz Cielniak
RA-L 2018

This letter presents an automated method for creating spatial maps of soil condition with an outdoor mobile robot. Effective soil mapping on farms can enhance yields, reduce inputs, and help protect the environment. Traditionally, data are collected manually at an arbitrary set of locations, then so

Cited by 34Source ↗Scholar ↗
2018

Analysis of Morphology-Based Features for Classification of Crop and Weeds in Precision Agriculture

Petra Bosilj, Tom Duckett, Grzegorz Cielniak
RA-L 2018

Determining the types of vegetation present in an image is a core step in many precision agriculture tasks. In this letter, we focus on pixel-based approaches for classification of crops versus weeds, especially for complex cases involving overlapping plants and partial occlusion. We examine the ben

Cited by 36Source ↗Scholar ↗
2018

Integrating Deep Semantic Segmentation Into 3-D Point Cloud Registration

Anestis Zaganidis, Li Sun, Tom Duckett, Grzegorz Cielniak
RA-L 2018

Point cloud registration is the task of aligning 3D scans of the same environment captured from different poses. When semantic information is available for the points, it can be used as a prior in the search for correspondences to improve registration. Semantic-assisted Normal Distributions Transfor

Cited by 78Source ↗Scholar ↗
2017

Semantic-assisted 3D normal distributions transform for scan registration in environments with limited structure

Anestis Zaganidis, Martin Magnusson, Tom Duckett, Grzegorz Cielniak
IROS 2017poster

Point cloud registration is a core problem of many robotic applications, including simultaneous localization and mapping. The Normal Distributions Transform (NDT) is a method that fits a number of Gaussian distributions to the data points, and then uses this transform as an approximation of the real…

Cited by 54Source ↗Scholar ↗
2016

Can you pick a broccoli? 3D-vision based detection and localisation of broccoli heads in the field

Keerthy Kusumam, Tomáš Krajník, Simon Pearson, Grzegorz Cielniak, Tom Duckett
IROS 2016poster

This paper presents a 3D vision system for robotic harvesting of broccoli using low-cost RGB-D sensors. The presented method addresses the tasks of detecting mature broccoli heads in the field and providing their 3D locations relative to the vehicle. The paper evaluates different 3D features, machin…

Cited by 39Source ↗Scholar ↗