I. Kamon

789 total citations
11 papers, 519 citations indexed

About

I. Kamon is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, I. Kamon has authored 11 papers receiving a total of 519 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Aerospace Engineering, 8 papers in Computer Vision and Pattern Recognition and 4 papers in Artificial Intelligence. Recurrent topics in I. Kamon's work include Robotics and Sensor-Based Localization (9 papers), Robotic Path Planning Algorithms (8 papers) and Distributed Control Multi-Agent Systems (3 papers). I. Kamon is often cited by papers focused on Robotics and Sensor-Based Localization (9 papers), Robotic Path Planning Algorithms (8 papers) and Distributed Control Multi-Agent Systems (3 papers). I. Kamon collaborates with scholars based in Israel, Germany and United Kingdom. I. Kamon's co-authors include Ehud Rivlin, Elon Rimon, Tamar Flash, Shimon Edelman, Shimon Edelman, Amir Navot and Anthony Narkawicz and has published in prestigious journals such as The International Journal of Robotics Research, IEEE Transactions on Robotics and Automation and IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans.

In The Last Decade

I. Kamon

11 papers receiving 469 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
I. Kamon Israel	7	414	274	220	124	73	11	519
R. Zapata France	12	306 0.7×	184 0.7×	226 1.0×	93 0.8×	78 1.1×	65	485
Yong K. Hwang United States	4	529 1.3×	272 1.0×	267 1.2×	68 0.5×	46 0.6×	6	620
Ahmad A. Masoud Saudi Arabia	15	538 1.3×	335 1.2×	338 1.5×	189 1.5×	60 0.8×	61	680
Y.K. Hwang United States	8	601 1.5×	333 1.2×	353 1.6×	82 0.7×	65 0.9×	24	710
Federico Augugliaro Switzerland	9	327 0.8×	239 0.9×	204 0.9×	149 1.2×	56 0.8×	9	574
Hoseong Seo South Korea	13	393 0.9×	274 1.0×	356 1.6×	100 0.8×	91 1.2×	28	606
Angela Schöllig Switzerland	9	251 0.6×	312 1.1×	371 1.7×	101 0.8×	37 0.5×	10	611
Andreas Breitenmoser Switzerland	14	371 0.9×	262 1.0×	118 0.5×	312 2.5×	59 0.8×	25	648
Michael Shomin United States	9	414 1.0×	314 1.1×	487 2.2×	106 0.9×	165 2.3×	13	723
Soonkyum Kim United States	11	270 0.7×	137 0.5×	213 1.0×	106 0.9×	60 0.8×	22	417

Countries citing papers authored by I. Kamon

Since Specialization

Citations

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

Fields of papers citing papers by I. Kamon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of I. Kamon

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

All Works

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11 of 11 papers shown

1.

Narkawicz, Anthony, et al.. (2021). A Vision-based Solution to Estimating Time to Closest Point of Approach for Sense and Avoid. AIAA Scitech 2021 Forum. 4 indexed citations

2.

Kamon, I., Elon Rimon, & Ehud Rivlin. (2003). Range-sensor based navigation in three dimensions. 1. 163–169. 31 indexed citations

3.

Kamon, I., Ehud Rivlin, & Elon Rimon. (2002). A new range-sensor based globally convergent navigation algorithm for mobile robots. 1. 429–435. 93 indexed citations

4.

Kamon, I. & Ehud Rivlin. (2002). Sensory based motion planning with global proofs. 2. 435–440. 13 indexed citations

5.

Kamon, I., Tamar Flash, & Shimon Edelman. (2002). Learning to grasp using visual information. 3. 2470–2476. 69 indexed citations

6.

Kamon, I., Elon Rimon, & Ehud Rivlin. (2001). Range-Sensor-Based Navigation in Three-Dimensional Polyhedral Environments. The International Journal of Robotics Research. 20(1). 6–25. 3 indexed citations

7.

Kamon, I., Tamar Flash, & Shimon Edelman. (1998). Learning visually guided grasping: a test case in sensorimotor learning. IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans. 28(3). 266–276. 18 indexed citations

8.

Kamon, I.. (1998). Tangent Bug : A Range-Sensor-Based Navigation Algorithm. Medical Entomology and Zoology. 17(9). 934–953. 3 indexed citations

9.

Kamon, I., Elon Rimon, & Ehud Rivlin. (1998). TangentBug: A Range-Sensor-Based Navigation Algorithm. The International Journal of Robotics Research. 17(9). 934–953. 126 indexed citations

10.

Kamon, I. & Ehud Rivlin. (1997). Sensory-based motion planning with global proofs. IEEE Transactions on Robotics and Automation. 13(6). 814–822. 158 indexed citations

11.

Kamon, I., Ehud Rivlin, & Elon Rimon. (1996). A New Range-Sensor Based Globally Algorithm for Mobile. 1 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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