Tine Lefebvre

24 papers receiving 819 citations

Peers

Tine Lefebvre
Comparison fields: 5 of 68
  • Artificial Intelligence 476
  • Control and Systems Engineering 471
  • Aerospace Engineering 266
  • Mechanical Engineering 142
  • Biomedical Engineering 134
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Fei Xie China
Fernando Figueroa United States
Chenkun Qi China
Shaohua Tan Singapore
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Citations per year

Countries citing papers authored by Tine Lefebvre

Since Specialization
Citations

This map shows the geographic impact of Tine Lefebvre's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tine Lefebvre with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tine Lefebvre more than expected).

Fields of papers citing papers by Tine Lefebvre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tine Lefebvre. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tine Lefebvre. The network helps show where Tine Lefebvre may publish in the future.

Co-authorship network of co-authors of Tine Lefebvre

This figure shows the co-authorship network connecting the top 25 collaborators of Tine Lefebvre. A scholar is included among the top collaborators of Tine Lefebvre based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tine Lefebvre. Tine Lefebvre is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 14
2 47
3 7
4 17
5 67
6 49
7 21
8 1
9
Non-linear autonomous compliant motion with a non-minimal state Kalman filter
0
10
A Rigorous Bayesian Approach to Simultaneous Model Selection and State Estimation
3
11
A comparison of decision making criteria and optimization methods for active robotic sensing
9
12
Contact modelling, parameter identification and task planning for autonomous compliant motion using elementary contacts
9
13 34
14 13
15 2
16
An open software framework for Bayesian state and parameter estimation
0
17
Tracking contact transitions during force-controlled compliant motion using an interacting multiple model estimator
2
18
Estimation and Propagation of Geometrical Parameters During Force-Controlled Execution of Polyhedral Contact Formation Sequences
2
19
Kalman Filters : A Tutorial
22
20 67

About Tine Lefebvre

Tine Lefebvre is a scholar working on Control and Systems Engineering, Industrial and Manufacturing Engineering and Artificial Intelligence, having authored 27 papers that have together received 885 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (19 papers), Teleoperation and Haptic Systems (7 papers) and Target Tracking and Data Fusion in Sensor Networks (6 papers). The work is most often cited by research in Control and Systems Engineering (471 citations), Artificial Intelligence (476 citations) and Aerospace Engineering (266 citations). Tine Lefebvre has collaborated with scholars based in Belgium, Australia and United States. Frequent co-authors include Herman Bruyninckx, Joris De Schutter, Klaas Gadeyne, Jing Xiao, Jayantha Katupitiya, Lyudmila Mihaylova, Johan Rutgeerts, Ernesto Staffetti, Juliang Xiao and Peter Slaets. Their work appears in journals such as IEEE Transactions on Automatic Control, The International Journal of Robotics Research and IEEE Transactions on Robotics and Automation.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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