S.N. Gottschlich

488 citations
22 papers · 343 · h-index 7

Impact in

Papers in

S.N. Gottschlich

18 papers receiving 311 citations

Peers

S.N. Gottschlich
Comparison fields: 5 of 50
  • Industrial and Manufacturing Engineering 133
  • Geology 64
  • Computer Graphics and Computer-Aided Design 30
  • Computer Vision and Pattern Recognition 160
  • Aerospace Engineering 112
Replace Soohwan Song with:
Soohwan Song South Korea
Cheng Jiang China
Xiaoxi Gong China
Fen Fang Singapore
Feixiang Lu China
Guoxiong Hu China
Tolga Birdal United States
Ramanpreet Singh Pahwa Singapore
Oliver Wulf Germany
Jianhui Liu China
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Citations per field
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Citations per year

Countries citing papers authored by S.N. Gottschlich

Since Specialization
Citations

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

Fields of papers citing papers by S.N. Gottschlich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S.N. Gottschlich. 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 S.N. Gottschlich. The network helps show where S.N. Gottschlich may publish in the future.

Co-authors

The 10 scholars most cited alongside S.N. Gottschlich, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with S.N. Gottschlich Line = papers co-authored together S.N. Gottschlich links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995134
2 199448
3 199039
4 198935
5 199526
6 200211
7 20027
8
Dealing with uncertainties in cad-based assembly motion planning
19916
9 19946
10 20026
11 20026
12 20025
13 20034
14 20023
15 20033
16 20022
17
AMP-CAD: automatic assembly motion planning using CAD models of parts
19921
18 20021
19 20050
20 20050

About S.N. Gottschlich

S.N. Gottschlich is a scholar working on Control and Systems Engineering, Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition, Biomedical Engineering and Aerospace Engineering, having authored 22 papers that have together received 343 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (14 papers), Manufacturing Process and Optimization (11 papers), Robotic Path Planning Algorithms (6 papers), Soft Robotics and Applications (4 papers), Robotics and Sensor-Based Localization (3 papers), Industrial Vision Systems and Defect Detection (3 papers), Robotic Mechanisms and Dynamics (2 papers) and Teleoperation and Haptic Systems (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (133 citations), Geology (64 citations), Computer Graphics and Computer-Aided Design (30 citations), Computer Vision and Pattern Recognition (160 citations) and Aerospace Engineering (112 citations). S.N. Gottschlich has collaborated with scholars based in United States and Portugal. Frequent co-authors include A.C. Kak, Carlos Ramos, Damian M. Lyons, R.J. Safranek, Stavros Vougioukas, Lester A. Gerhardt, Himmat Singh, J.R. Babb, Laxman Singh and H.E. Stephanou. Their work appears in journals such as Computer Vision and Image Understanding, Robotics and Autonomous Systems, IEEE Transactions on Robotics and Automation, IEEE Robotics & Automation Magazine and Purdue e-Pubs (Purdue University System).

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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