Juan-Manuel Ahuactzin

403 total citations
10 papers, 211 citations indexed

About

Juan-Manuel Ahuactzin is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Artificial Intelligence. According to data from OpenAlex, Juan-Manuel Ahuactzin has authored 10 papers receiving a total of 211 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 7 papers in Control and Systems Engineering and 3 papers in Artificial Intelligence. Recurrent topics in Juan-Manuel Ahuactzin's work include Robotic Path Planning Algorithms (8 papers), Robot Manipulation and Learning (5 papers) and Robotic Mechanisms and Dynamics (3 papers). Juan-Manuel Ahuactzin is often cited by papers focused on Robotic Path Planning Algorithms (8 papers), Robot Manipulation and Learning (5 papers) and Robotic Mechanisms and Dynamics (3 papers). Juan-Manuel Ahuactzin collaborates with scholars based in France, Mexico and Canada. Juan-Manuel Ahuactzin's co-authors include Kamal Gupta, Thierry Fraichard, Emmanuel Mazer, Pierre Bessìère, El‐Ghazali Talbi, Kamel Mekhnacha, Linda Smail and Christian Laugier and has published in prestigious journals such as IEEE Transactions on Robotics and Automation, Revue d intelligence artificielle and HAL (Le Centre pour la Communication Scientifique Directe).

In The Last Decade

Juan-Manuel Ahuactzin

10 papers receiving 194 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Juan-Manuel Ahuactzin France	6	160	137	82	36	18	10	211
Andrew Dobson United States	9	160 1.0×	96 0.7×	77 0.9×	47 1.3×	19 1.1×	11	205
Gisbert Lawitzky Germany	9	166 1.0×	87 0.6×	105 1.3×	28 0.8×	33 1.8×	14	222
Marco Morales United States	9	165 1.0×	69 0.5×	97 1.2×	30 0.8×	14 0.8×	28	202
Albert J. Wavering United States	9	83 0.5×	72 0.5×	40 0.5×	22 0.6×	30 1.7×	20	185
T. Skewis United States	5	242 1.5×	101 0.7×	163 2.0×	24 0.7×	26 1.4×	8	269
Tobia Marcucci United States	8	125 0.8×	111 0.8×	28 0.3×	35 1.0×	48 2.7×	10	205
Tobias Kunz United States	7	165 1.0×	190 1.4×	45 0.5×	53 1.5×	89 4.9×	10	291
Jung-Su Ha South Korea	10	104 0.7×	115 0.8×	54 0.7×	53 1.5×	26 1.4×	27	216
Jory Denny United States	10	209 1.3×	90 0.7×	141 1.7×	32 0.9×	17 0.9×	20	235
Qingni Yuan China	10	134 0.8×	90 0.7×	61 0.7×	30 0.8×	10 0.6×	19	251

Countries citing papers authored by Juan-Manuel Ahuactzin

Since Specialization

Citations

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

Fields of papers citing papers by Juan-Manuel Ahuactzin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Juan-Manuel Ahuactzin. 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 Juan-Manuel Ahuactzin. The network helps show where Juan-Manuel Ahuactzin may publish in the future.

Co-authorship network of co-authors of Juan-Manuel Ahuactzin

This figure shows the co-authorship network connecting the top 25 collaborators of Juan-Manuel Ahuactzin. A scholar is included among the top collaborators of Juan-Manuel Ahuactzin 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 Juan-Manuel Ahuactzin. Juan-Manuel Ahuactzin 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

Mekhnacha, Kamel, Juan-Manuel Ahuactzin, Pierre Bessìère, Emmanuel Mazer, & Linda Smail. (2007). Exact and approximate inference in ProBT. Revue d intelligence artificielle. 21(3). 295–332. 9 indexed citations

Mekhnacha, Kamel, Linda Smail, Juan-Manuel Ahuactzin, Pierre Bessìère, & Emmanuel Mazer. (2006). A unifying framework for exact and approximate Bayesian inference. HAL (Le Centre pour la Communication Scientifique Directe). 44. 1 indexed citations

Ahuactzin, Juan-Manuel & Kamal Gupta. (2003). Completeness results for a point-to-point inverse kinematics algorithm. 2. 1526–1531. 2 indexed citations

Ahuactzin, Juan-Manuel & Kamal Gupta. (2002). A motion planning based approach for inverse kinematics of redundant robots: the kinematic roadmap. 4. 3609–3614. 12 indexed citations

Ahuactzin, Juan-Manuel, et al.. (2002). A basic algorithm and data structures for sensor-based path planning in unknown environments. 2. 903–908. 14 indexed citations

Bessìère, Pierre, Juan-Manuel Ahuactzin, El‐Ghazali Talbi, & Emmanuel Mazer. (2002). The "Ariadne's clew" algorithm: global planning with local methods. 2. 1373–1380. 65 indexed citations

Fraichard, Thierry & Juan-Manuel Ahuactzin. (2002). Smooth path planning for cars. 4. 3722–3727. 39 indexed citations

Ahuactzin, Juan-Manuel, Kamal Gupta, & Emmanuel Mazer. (2002). On manipulation planning. 5. 67–72. 1 indexed citations

Ahuactzin, Juan-Manuel, et al.. (2002). Controlling virtual autonomous entities in dynamic environments using an appropriate sense-plan-control paradigm. 1. 163–168. 4 indexed citations

10.

Ahuactzin, Juan-Manuel & Kamal Gupta. (1999). The kinematic roadmap: a motion planning based global approach for inverse kinematics of redundant robots. IEEE Transactions on Robotics and Automation. 15(4). 653–669. 64 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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