Author details

< Back

Nataliya Strokina

Publications

Citations

Publications by Year

20122025

Co-Authors:

Alexandre AngleraudMohammad M. ArefKe ChenAtakan DagTuomas Eerola

Show All Co-Authors (24)

Nataliya Strokina

Affiliation

Faculty of Information Technology and Communication

Tampere University

Tampere, Finland

Publication Topics

Loop Closure,
Neural Network,
Point Cloud,
Simultaneous Localization And Mapping,
Active Control,
Actor Network,
Actual Values,
Angular Speed,
Attention Mechanism,
Attention Module,
Attention Network,
Bundle Adjustment

Biography

Nataliya Strokina received the M.Sc. degrees in software engineering and intelligent computing from Saint Petersburg Electrotechnical University, Saint Petersburg, Russia, Russian Federation and Lappeenranta University of Technology, Lappeenranta, Finland, correspondingly in 2009, and the Ph.D. degree in engineering and technology from the Lappeenranta University of Technology in 2013.,Since 2014, she has held a post-doctoral researcher position with the Tampere University of Technology, Tampere, Finland. Her current research interests include machine learning, image understanding, and currently development of the signal processing methods for underwater robotics.(Based on document published on 14 February 2017).

Publications

Citations

Publications by Year

20122025

Co-Authors:

Alexandre Angleraud
Mohammad M. Aref
Ke Chen
Atakan Dag
Tuomas Eerola

Show All Co-Authors (24)

Author's Published Works

Search History

Showing 1-9 of 9 results

Conferences (6)

Journals (3)

Sort

Filter Results

Show

All Results

Subscribed Content

Open Access Only

Range
Single Year
Nataliya Strokina(9)
Joni-Kristian Kämäräinen(5)
Reza Ghabcheloo(4)
Wenyan Yang(3)
Maarja Kruusmaa(3)
Computing Sciences, Tampere University, Finland(3)
Department of Signal Processing, Tampere University of Technology, Tampere, Finland(2)
Center of Biorobotics, Tallinn University of Technology, Tallinn, Estonia(2)
SJE Ecohydraulic Engineering GmbH, Stuttgart, Germany(2)
Automation Technology and Mechanical Engineering, Tampere University, Finland(2)
IEEE Transactions on Instrumentation and Measurement(2)
2015 IEEE International Conference on Robotics and Automation (ICRA)(1)
2020 IEEE International Conference on Robotics and Automation (ICRA)(1)
2021 IEEE International Conference on Robotics and Automation (ICRA)(1)
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)(1)
IEEE(9)
Media(3)
Linköping, Sweden(1)
Paris, France(1)
Prague, Czech Republic(1)
Seattle, WA, USA(1)
Tsukuba, Japan(1)
Flow Velocity(3)
Lateral Line(3)
Loop Closure(3)
Neural Network(3)
Piezoresistive Sensors(3)

Select All on Page

Sort By

Results

Representation Learning for Place Recognition Using MIMO Radar

Prashant Kumar Rai;Nataliya Strokina;Reza Ghabcheloo

IEEE Open Journal of Intelligent Transportation Systems

Year: 2025 | Volume: 6 | Journal Article |

HTML

Traditional radar perception often rely on point clouds derived from radar heatmap using CFAR filtering, which can result in the loss of valuable information, especially weaker signals crucial for accurate perception. To address this, we present a novel approach for representation learning directly from pre-CFAR heatmaps, specifically for place recognition using a high-resolution MIMO radar sensor...Show More

Representation Learning for Place Recognition Using MIMO Radar

Prashant Kumar Rai;Nataliya Strokina;Reza Ghabcheloo

IEEE Open Journal of Intelligent Transportation Systems

Year: 2025 | Volume: 6 | Journal Article |

Evaluation and comparison of eight popular Lidar and Visual SLAM algorithms

Bharath Garigipati;Nataliya Strokina;Reza Ghabcheloo

2022 25th International Conference on Information Fusion (FUSION)

Year: 2022 | Conference Paper |

Cited by: Papers (11)

HTML

In this paper, we evaluate eight popular and open-source 3D Lidar and visual SLAM (Simultaneous Localization and Mapping) algorithms, namely LOAM, Lego LOAM, LIO SAM, HDL Graph, ORB SLAM3, Basalt VIO, and SVO2. We have devised experiments both indoor and outdoor to investigate the effect of the following items: i) effect of mounting positions of the sensors, ii) effect of terrain type and vibratio...Show More

Evaluation and comparison of eight popular Lidar and Visual SLAM algorithms

Bharath Garigipati;Nataliya Strokina;Reza Ghabcheloo

2022 25th International Conference on Information Fusion (FUSION)

Year: 2022 | Conference Paper |

Monolithic vs. hybrid controller for multi-objective Sim-to-Real learning

Atakan Dag;Alexandre Angleraud;Wenyan Yang;Nataliya Strokina;Roel S. Pieters;Minna Lanz;Joni-Kristian Kämäräinen

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2021 | Conference Paper |

HTML

Simulation to real (Sim-to-Real) is an attractive approach to construct controllers for robotic tasks that are easier to simulate than to analytically solve. Working Sim-to-Real solutions have been demonstrated for tasks with a clear single objective such as "reach the target". Real world applications, however, often consist of multiple simultaneous objectives such as "reach the target" but "avoid...Show More

Monolithic vs. hybrid controller for multi-objective Sim-to-Real learning

Atakan Dag;Alexandre Angleraud;Wenyan Yang;Nataliya Strokina;Roel S. Pieters;Minna Lanz;Joni-Kristian Kämäräinen

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2021 | Conference Paper |

Neural Network Controller for Autonomous Pile Loading Revised

Wenyan Yang;Nataliya Strokina;Nikolay Serbenyuk;Joni Pajarinen;Reza Ghabcheloo;Juho Vihonen;Mohammad M. Aref;Joni-Kristian Kämäräinen

2021 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2021 | Conference Paper |

Cited by: Papers (6)

HTML

We have recently proposed two pile loading controllers that learn from human demonstrations: a neural network (NNet) [1] and a random forest (RF) controller [2]. In the field experiments the RF controller obtained clearly better success rates. In this work, the previous findings are drastically revised by experimenting summer time trained controllers in winter conditions. The winter experiments re...Show More

Neural Network Controller for Autonomous Pile Loading Revised

Wenyan Yang;Nataliya Strokina;Nikolay Serbenyuk;Joni Pajarinen;Reza Ghabcheloo;Juho Vihonen;Mohammad M. Aref;Joni-Kristian Kämäräinen

2021 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2021 | Conference Paper |

Learning a Pile Loading Controller from Demonstrations

Wenyan Yang;Nataliya Strokina;Nikolay Serbenyuk;Reza Ghabcheloo;Joni Kämäräinen

2020 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2020 | Conference Paper |

Cited by: Papers (4)

HTML

This work introduces a learning-based pile loading controller for autonomous robotic wheel loaders. Controller parameters are learnt from a small number of demonstrations for which low level sensor (boom angle, bucket angle and hydrostatic driving pressure), egocentric video frames and control signals are recorded. Application specific deep visual features are learnt from demonstrations using a Si...Show More

Learning a Pile Loading Controller from Demonstrations

Wenyan Yang;Nataliya Strokina;Nikolay Serbenyuk;Reza Ghabcheloo;Joni Kämäräinen

2020 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2020 | Conference Paper |

Estimation of Flow Turbulence Metrics With a Lateral Line Probe and Regression

Ke Chen;Jeffrey A. Tuhtan;Juan Fran Fuentes-Pérez;Gert Toming;Mark Musall;Nataliya Strokina;Joni-Kristian Kämäräinen;Maarja Kruusmaa

IEEE Transactions on Instrumentation and Measurement

Year: 2017 | Volume: 66, Issue: 4 | Journal Article |

Cited by: Papers (18)

HTML

The time-averaged velocity of water flow is the most commonly measured metric for both laboratory and field applications. Its employment in scientific and engineering studies often leads to an oversimplification of the underlying flow physics. In reality, complex flows are ubiquitous, and commonly arise from fluid-body interactions with man-made structures, such as bridges as well as from natural ...Show More

Estimation of Flow Turbulence Metrics With a Lateral Line Probe and Regression

Ke Chen;Jeffrey A. Tuhtan;Juan Fran Fuentes-Pérez;Gert Toming;Mark Musall;Nataliya Strokina;Joni-Kristian Kämäräinen;Maarja Kruusmaa

IEEE Transactions on Instrumentation and Measurement

Year: 2017 | Volume: 66, Issue: 4 | Journal Article |

Joint Estimation of Bulk Flow Velocity and Angle Using a Lateral Line Probe

Nataliya Strokina;Joni-Kristian Kämäräinen;Jeffrey A. Tuhtan;Juan Francisco Fuentes-Pérez;Maarja Kruusmaa

IEEE Transactions on Instrumentation and Measurement

Year: 2016 | Volume: 65, Issue: 3 | Journal Article |

Cited by: Papers (31)

HTML

Measurement of complex natural flows, especially those occurring in rivers due to man-made structures, is often hampered by the limitations of existing flow measurement methods. Furthermore, there is a growing need for new measurement devices that are capable of measuring the hydrodynamic characteristics of complex natural flows required in environmental studies that often use fish as an indicator...Show More

Joint Estimation of Bulk Flow Velocity and Angle Using a Lateral Line Probe

Nataliya Strokina;Joni-Kristian Kämäräinen;Jeffrey A. Tuhtan;Juan Francisco Fuentes-Pérez;Maarja Kruusmaa

IEEE Transactions on Instrumentation and Measurement

Year: 2016 | Volume: 65, Issue: 3 | Journal Article |

Flow feature extraction for underwater robot localization: Preliminary results

Naveed Muhammad;Nataliya Strokina;Gert Toming;Jeffrey Tuhtan;Joni-Kristian Kämäräinen;Maarja Kruusmaa

2015 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2015 | Conference Paper |

Cited by: Papers (11)

HTML

Underwater robots conventionally use vision and sonar sensors for perception purposes, but recently bio-inspired sensors that can sense flow have been developed. In literature, flow sensing has been shown to provide useful information about an underwater object and its surroundings. In the light of this, we develop an underwater landmark recognition technique which is based on the extraction and c...Show More

Flow feature extraction for underwater robot localization: Preliminary results

Naveed Muhammad;Nataliya Strokina;Gert Toming;Jeffrey Tuhtan;Joni-Kristian Kämäräinen;Maarja Kruusmaa

2015 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2015 | Conference Paper |

Detection of bubbles as Concentric Circular Arrangements

Nataliya Strokina;Jiri Matas;Tuomas Eerola;Lasse Lensu;Heikki Kälviäinen

Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012)

Year: 2012 | Conference Paper |

HTML

A method for the detection of bubble-like transparent objects with multiple interfaces in a liquid is proposed. Depending on the lighting conditions, bubble appearance varies significantly, including contrast reversal and multiple inter-reflections. We formulate the bubble detection problem as the detection of Concentric Circular Arrangements (CCA). The CCAs are recovered in a hypothesize-optimize...Show More

Detection of bubbles as Concentric Circular Arrangements

Nataliya Strokina;Jiri Matas;Tuomas Eerola;Lasse Lensu;Heikki Kälviäinen

Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012)

Year: 2012 | Conference Paper |

MIT Libraries

MIT Libraries

Author details

Nataliya Strokina

Nataliya Strokina

Affiliation

Publication Topics

Biography

Showing 1-9 of 9 results

Show

Representation Learning for Place Recognition Using MIMO Radar

Representation Learning for Place Recognition Using MIMO Radar

Evaluation and comparison of eight popular Lidar and Visual SLAM algorithms

Evaluation and comparison of eight popular Lidar and Visual SLAM algorithms

Monolithic vs. hybrid controller for multi-objective Sim-to-Real learning

Monolithic vs. hybrid controller for multi-objective Sim-to-Real learning

Neural Network Controller for Autonomous Pile Loading Revised

Neural Network Controller for Autonomous Pile Loading Revised

Learning a Pile Loading Controller from Demonstrations

Learning a Pile Loading Controller from Demonstrations

Estimation of Flow Turbulence Metrics With a Lateral Line Probe and Regression

Estimation of Flow Turbulence Metrics With a Lateral Line Probe and Regression

Joint Estimation of Bulk Flow Velocity and Angle Using a Lateral Line Probe

Joint Estimation of Bulk Flow Velocity and Angle Using a Lateral Line Probe

Flow feature extraction for underwater robot localization: Preliminary results

Flow feature extraction for underwater robot localization: Preliminary results

Detection of bubbles as Concentric Circular Arrangements

Detection of bubbles as Concentric Circular Arrangements

IEEE Account

Purchase Details

Profile Information

Need Help?