Robert Paolini

652 total citations
10 papers, 398 citations indexed

About

Robert Paolini is a scholar working on Control and Systems Engineering, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Robert Paolini has authored 10 papers receiving a total of 398 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Control and Systems Engineering, 4 papers in Biomedical Engineering and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Robert Paolini's work include Robot Manipulation and Learning (8 papers), Robotic Mechanisms and Dynamics (6 papers) and Motor Control and Adaptation (2 papers). Robert Paolini is often cited by papers focused on Robot Manipulation and Learning (8 papers), Robotic Mechanisms and Dynamics (6 papers) and Motor Control and Adaptation (2 papers). Robert Paolini collaborates with scholars based in United States and Switzerland. Robert Paolini's co-authors include Matthew T. Mason, Siddhartha S Srinivasa, Nikhil Chavan-Dafle, Ivan Lundberg, Alberto Rodríguez, Michael Erdmann, Thomas Fuhlbrigge, Harald Staab, J. Andrew Bagnell and Drew Bagnell and has published in prestigious journals such as The International Journal of Robotics Research, IEEE Robotics and Automation Letters and DSpace@MIT (Massachusetts Institute of Technology).

In The Last Decade

Robert Paolini

10 papers receiving 383 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Robert Paolini United States	9	355	209	100	98	58	10	398
L. Han China	7	349 1.0×	217 1.0×	58 0.6×	106 1.1×	15 0.3×	14	393
Alexander Alspach United States	9	168 0.5×	199 1.0×	48 0.5×	105 1.1×	37 0.6×	13	331
Marek Kopicki United Kingdom	11	322 0.9×	173 0.8×	138 1.4×	90 0.9×	80 1.4×	18	414
Wen‐Han Qian China	11	250 0.7×	147 0.7×	43 0.4×	55 0.6×	28 0.5×	34	327
Viktor Makoviychuk United Kingdom	8	196 0.6×	61 0.3×	83 0.8×	33 0.3×	59 1.0×	10	260
Yuqiang Wu China	11	335 0.9×	129 0.6×	30 0.3×	114 1.2×	26 0.4×	23	427
Jeffrey C. Trinkle United States	8	314 0.9×	115 0.6×	42 0.4×	71 0.7×	25 0.4×	17	366
Nima Fazeli United States	9	117 0.3×	109 0.5×	46 0.5×	37 0.4×	45 0.8×	31	305
Adrià Colomé Spain	11	349 1.0×	178 0.9×	103 1.0×	101 1.0×	98 1.7×	32	449
James M. Bern Switzerland	10	203 0.6×	239 1.1×	67 0.7×	150 1.5×	36 0.6×	15	401

Countries citing papers authored by Robert Paolini

Since Specialization

Citations

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

Fields of papers citing papers by Robert Paolini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert Paolini

This figure shows the co-authorship network connecting the top 25 collaborators of Robert Paolini. A scholar is included among the top collaborators of Robert Paolini 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 Robert Paolini. Robert Paolini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

Mason, Matthew T., et al.. (2018). A convex polynomial model for planar sliding mechanics: theory, application, and experimental validation. The International Journal of Robotics Research. 37(2-3). 249–265. 34 indexed citations

2.

Paolini, Robert, et al.. (2017). A Probabilistic Planning Framework for Planar Grasping Under Uncertainty. IEEE Robotics and Automation Letters. 2(4). 2111–2118. 19 indexed citations

3.

Paolini, Robert, et al.. (2016). A convex polynomial force-motion model for planar sliding: Identification and application. 372–377. 52 indexed citations

4.

Paolini, Robert & Matthew T. Mason. (2016). Data-driven statistical modeling of a cube regrasp. 11. 2554–2560. 6 indexed citations

5.

Paolini, Robert, et al.. (2015). A general framework for open-loop pivoting. 3675–3681. 30 indexed citations

6.

Chavan-Dafle, Nikhil, Alberto Rodríguez, Robert Paolini, et al.. (2014). Extrinsic dexterity: In-hand manipulation with external forces. 8 indexed citations

7.

Paolini, Robert, Alberto Rodríguez, Siddhartha S Srinivasa, & Matthew T. Mason. (2014). A data-driven statistical framework for post-grasp manipulation. The International Journal of Robotics Research. 33(4). 600–615. 27 indexed citations

8.

Chavan-Dafle, Nikhil, Alberto Rodríguez, Robert Paolini, et al.. (2014). Regrasping objects using extrinsic dexterity. 2560–2560. 11 indexed citations

9.

Chavan-Dafle, Nikhil, Alberto Rodríguez, Robert Paolini, et al.. (2014). Extrinsic dexterity: In-hand manipulation with external forces. DSpace@MIT (Massachusetts Institute of Technology). 1578–1585. 199 indexed citations

10.

Backes, Paul, Nicolas Hudson, Curtis Collins, et al.. (2011). Experimental results of rover-based coring and caching. 1–14. 12 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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