Vladimir Ivan

643 total citations
30 papers, 336 citations indexed

About

Vladimir Ivan is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Aerospace Engineering. According to data from OpenAlex, Vladimir Ivan has authored 30 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 19 papers in Control and Systems Engineering and 13 papers in Aerospace Engineering. Recurrent topics in Vladimir Ivan's work include Robotic Path Planning Algorithms (18 papers), Robotics and Sensor-Based Localization (13 papers) and Robot Manipulation and Learning (11 papers). Vladimir Ivan is often cited by papers focused on Robotic Path Planning Algorithms (18 papers), Robotics and Sensor-Based Localization (13 papers) and Robot Manipulation and Learning (11 papers). Vladimir Ivan collaborates with scholars based in United Kingdom, Spain and Germany. Vladimir Ivan's co-authors include Sethu Vijayakumar, Wolfgang Merkt, Yiming Yang, Taku Komura, Marc Toussaint, Zhibin Li, Ioannis Havoutis, Leopoldo Armesto, Eduardo Ros and Karl Pauwels and has published in prestigious journals such as Sensors, The International Journal of Robotics Research and IEEE Transactions on Robotics.

In The Last Decade

Vladimir Ivan

29 papers receiving 322 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Vladimir Ivan United Kingdom 13 209 196 132 113 47 30 336
Lars‐Peter Ellekilde Denmark 13 121 0.6× 247 1.3× 87 0.7× 97 0.9× 75 1.6× 36 388
Gregory Kahn United States 6 157 0.8× 84 0.4× 90 0.7× 128 1.1× 26 0.6× 10 321
Nikita Rudin Switzerland 9 135 0.6× 154 0.8× 240 1.8× 75 0.7× 68 1.4× 12 438
Oliver Birbach Germany 9 122 0.6× 142 0.7× 90 0.7× 88 0.8× 29 0.6× 14 257
Hyunsoo Yang South Korea 10 158 0.8× 196 1.0× 59 0.4× 127 1.1× 67 1.4× 19 330
Fadri Furrer Switzerland 9 176 0.8× 184 0.9× 67 0.5× 116 1.0× 35 0.7× 12 353
Ziyuan Jiao China 11 143 0.7× 125 0.6× 62 0.5× 85 0.8× 34 0.7× 22 278
E. Tunstel United States 9 176 0.8× 108 0.6× 68 0.5× 129 1.1× 79 1.7× 22 329
Victor M. Vega Spain 9 241 1.2× 279 1.4× 96 0.7× 217 1.9× 80 1.7× 10 473
Tingguang Li Hong Kong 9 200 1.0× 95 0.5× 47 0.4× 126 1.1× 28 0.6× 17 295

Countries citing papers authored by Vladimir Ivan

Since Specialization
Citations

This map shows the geographic impact of Vladimir Ivan'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 Vladimir Ivan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vladimir Ivan more than expected).

Fields of papers citing papers by Vladimir Ivan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vladimir Ivan. 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 Vladimir Ivan. The network helps show where Vladimir Ivan may publish in the future.

Co-authorship network of co-authors of Vladimir Ivan

This figure shows the co-authorship network connecting the top 25 collaborators of Vladimir Ivan. A scholar is included among the top collaborators of Vladimir Ivan 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 Vladimir Ivan. Vladimir Ivan 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
1.
Wang, Jiayi, Sang-Hyun Kim, Vladimir Ivan, et al.. (2024). Online Multicontact Receding Horizon Planning via Value Function Approximation. IEEE Transactions on Robotics. 40. 2791–2810. 3 indexed citations
2.
Ivan, Vladimir, et al.. (2023). RoLoMa: robust loco-manipulation for quadruped robots with arms. Autonomous Robots. 47(8). 1463–1481. 30 indexed citations
3.
Zhang, Tianwei, et al.. (2022). RGB-D SLAM in Indoor Planar Environments With Multiple Large Dynamic Objects. IEEE Robotics and Automation Letters. 7(3). 8209–8216. 18 indexed citations
4.
Llamazares, Ángel, Eduardo Molinos, Manuel Ocaña, & Vladimir Ivan. (2020). Improved Dynamic Obstacle Mapping (iDOMap). Sensors. 20(19). 5520–5520.
5.
Ivan, Vladimir, et al.. (2019). Learning-driven Coarse-to-Fine Articulated Robot Tracking. Edinburgh Research Explorer. 6604–6610. 4 indexed citations
6.
Merkt, Wolfgang, Vladimir Ivan, & Sethu Vijayakumar. (2019). Continuous-Time Collision Avoidance for Trajectory Optimization in Dynamic Environments. Edinburgh Research Explorer. 7248–7255. 12 indexed citations
7.
Yang, Yiming, Wolfgang Merkt, Vladimir Ivan, & Sethu Vijayakumar. (2018). Planning in Time-Configuration Space for Efficient Pick-and-Place in Non-Static Environments with Temporal Constraints. Edinburgh Research Explorer. 1–9. 12 indexed citations
8.
Merkt, Wolfgang, et al.. (2018). Whole-Body End-Pose Planning for Legged Robots on Inclined Support Surfaces in Complex Environments. Edinburgh Research Explorer. 944–951. 5 indexed citations
9.
Fisher, R. S., Benjamin Rosman, & Vladimir Ivan. (2018). Real-Time Motion Planning in Changing Environments Using Topology-Based Encoding of Past Knowledge. Edinburgh Research Explorer. 3 indexed citations
10.
Yang, Yiming, et al.. (2017). HDRM: A Resolution Complete Dynamic Roadmap for Real-Time Motion Planning in Complex Scenes. IEEE Robotics and Automation Letters. 3(1). 551–558. 14 indexed citations
11.
Armesto, Leopoldo, et al.. (2017). Learning Constrained Generalizable Policies by Demonstration. Edinburgh Research Explorer (University of Edinburgh). 6 indexed citations
12.
Yang, Yiming, et al.. (2017). Efficient Humanoid Motion Planning on Uneven Terrain Using Paired Forward-Inverse Dynamic Reachability Maps. IEEE Robotics and Automation Letters. 2(4). 2279–2286. 23 indexed citations
13.
Yang, Yiming, Vladimir Ivan, Zhibin Li, Maurice Fallon, & Sethu Vijayakumar. (2016). iDRM: Humanoid motion planning with realtime end-pose selection in complex environments. Edinburgh Research Explorer (University of Edinburgh). 271–278. 20 indexed citations
14.
Yang, Yiming, Vladimir Ivan, Wolfgang Merkt, & Sethu Vijayakumar. (2016). Scaling sampling-based motion planning to humanoid robots. Edinburgh Research Explorer. 1448–1454. 22 indexed citations
15.
Yang, Yiming, Vladimir Ivan, & Sethu Vijayakumar. (2015). Real-time motion adaptation using relative distance space representation. Edinburgh Research Explorer. 29. 21–27. 12 indexed citations
16.
Pauwels, Karl, Vladimir Ivan, Eduardo Ros, & Sethu Vijayakumar. (2014). Real-time object pose recognition and tracking with an imprecisely calibrated moving RGB-D camera. Edinburgh Research Explorer (University of Edinburgh). 20 indexed citations
17.
Pauwels, Karl, et al.. (2014). Real-time RGB-D-based Object and Manipulator Pose Estimation. 1 indexed citations
18.
Ivan, Vladimir, et al.. (2013). Dexterous reaching, grasp transfer and planning using electrostatic representations. 1. 211–218. 5 indexed citations
19.
Ivan, Vladimir, et al.. (2012). Hierarchical Motion Planning in Topological Representations. 18 indexed citations
20.
Ivan, Vladimir, et al.. (2012). 2012 Robotics: Science and Systems (R:SS) Conference. 3 indexed citations

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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