Daniel Kappler

1.3k total citations
20 papers, 555 citations indexed

About

Daniel Kappler is a scholar working on Control and Systems Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Daniel Kappler has authored 20 papers receiving a total of 555 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Control and Systems Engineering, 8 papers in Artificial Intelligence and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Daniel Kappler's work include Robot Manipulation and Learning (12 papers), Reinforcement Learning in Robotics (6 papers) and Robotics and Sensor-Based Localization (3 papers). Daniel Kappler is often cited by papers focused on Robot Manipulation and Learning (12 papers), Reinforcement Learning in Robotics (6 papers) and Robotics and Sensor-Based Localization (3 papers). Daniel Kappler collaborates with scholars based in Germany, United States and Spain. Daniel Kappler's co-authors include Stefan Schaal, Jeannette Bohg, Manuel Wüthrich, Tamim Asfour, Stefan Schaal, Nathan Ratliff, Franziska Meier, Fei Xia, Michael S. Ryoo and Kanishka Rao and has published in prestigious journals such as The International Journal of Robotics Research, Robotics and Autonomous Systems and IEEE Robotics and Automation Letters.

In The Last Decade

Daniel Kappler

20 papers receiving 523 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Kappler Germany 12 393 198 189 168 75 20 555
Matteo Saveriano Italy 13 391 1.0× 191 1.0× 158 0.8× 161 1.0× 41 0.5× 65 609
Kai Huebner Sweden 11 474 1.2× 240 1.2× 194 1.0× 114 0.7× 110 1.5× 22 583
Balakumar Sundaralingam United States 12 345 0.9× 206 1.0× 129 0.7× 107 0.6× 94 1.3× 17 482
Fu-Jen Chu United States 8 397 1.0× 169 0.9× 212 1.1× 103 0.6× 52 0.7× 10 509
Rudolf Lioutikov Germany 15 471 1.2× 184 0.9× 155 0.8× 271 1.6× 28 0.4× 24 661
Douglas Morrison Australia 4 266 0.7× 129 0.7× 153 0.8× 85 0.5× 78 1.0× 5 396
Koichi Ogawara Japan 15 396 1.0× 344 1.7× 232 1.2× 118 0.7× 66 0.9× 53 686
Ulrich Klank Germany 11 264 0.7× 288 1.5× 85 0.4× 169 1.0× 125 1.7× 17 573
Minghao Gou China 8 507 1.3× 353 1.8× 246 1.3× 188 1.1× 83 1.1× 12 783
Zhixing Xue Germany 11 309 0.8× 173 0.9× 149 0.8× 54 0.3× 91 1.2× 24 409

Countries citing papers authored by Daniel Kappler

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Kappler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Kappler

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Kappler. A scholar is included among the top collaborators of Daniel Kappler 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 Daniel Kappler. Daniel Kappler 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.
Chen, Boyuan, Fei Xia, Brian Ichter, et al.. (2023). Open-vocabulary Queryable Scene Representations for Real World Planning. 11509–11522. 82 indexed citations
2.
Jang, Eric, Daniel Kappler, Mohi Khansari, et al.. (2020). Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards. arXiv (Cornell University). 3 indexed citations
3.
Kappler, Daniel, et al.. (2019). Predicting grasp success in the real world - A study of quality metrics and human assessment. Robotics and Autonomous Systems. 121. 103274–103274. 5 indexed citations
4.
Kappler, Daniel, et al.. (2018). A case study of a framework for user-centered hardware development based on the aCar electric vehicle project. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 1–8. 3 indexed citations
5.
Kappler, Daniel, Franziska Meier, Jan Issac, et al.. (2018). Real-Time Perception Meets Reactive Motion Generation. IEEE Robotics and Automation Letters. 3(3). 1864–1871. 59 indexed citations
6.
Kappler, Daniel, et al.. (2017). On the relevance of grasp metrics for predicting grasp success. 265–272. 17 indexed citations
7.
8.
Kappler, Daniel, Stefan Schaal, & Jeannette Bohg. (2016). Optimizing for what matters: The top grasp hypothesis. 2167–2174. 2 indexed citations
9.
Bohg, Jeannette, Daniel Kappler, & Stefan Schaal. (2016). Exemplar-based prediction of global object shape from local shape similarity. 12. 3398–3405. 1 indexed citations
10.
Meier, Franziska, Daniel Kappler, Nathan Ratliff, & Stefan Schaal. (2016). Towards robust online inverse dynamics learning. 22 indexed citations
11.
Wüthrich, Manuel, et al.. (2016). A new perspective and extension of the Gaussian Filter. The International Journal of Robotics Research. 35(14). 1731–1749. 11 indexed citations
12.
Kappler, Daniel, et al.. (2016). Robot arm pose estimation by pixel-wise regression of joint angles. 616–623. 25 indexed citations
13.
Kappler, Daniel, et al.. (2016). Learning where to search using visual attention. 5238–5245. 34 indexed citations
14.
Wüthrich, Manuel, Sebastian Trimpe, Daniel Kappler, & Stefan Schaal. (2015). A New Perspective and Extension of the Gaussian Filter. 4 indexed citations
15.
Kappler, Daniel, Jeannette Bohg, & Stefan Schaal. (2015). Leveraging big data for grasp planning. 4304–4311. 160 indexed citations
16.
Kappler, Daniel, Peter Pástor, Mrinal Kalakrishnan, Manuel Wüthrich, & Stefan Schaal. (2015). Data-Driven Online Decision Making for Autonomous Manipulation. 36 indexed citations
17.
Ulbrich, Stefan, Daniel Kappler, Tamim Asfour, et al.. (2011). The OpenGRASP benchmarking suite: An environment for the comparative analysis of grasping and dexterous manipulation. 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems. 4 indexed citations
18.
Ulbrich, Stefan, Daniel Kappler, Tamim Asfour, et al.. (2011). The OpenGRASP benchmarking suite: An environment for the comparative analysis of grasping and dexterous manipulation. 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems. 1761–1767. 31 indexed citations
19.
Kappler, Daniel, Lillian Chang, Nancy S. Pollard, Tamim Asfour, & Rüdiger Dillmann. (2011). Templates for pre-grasp sliding interactions. Robotics and Autonomous Systems. 60(3). 411–423. 23 indexed citations
20.
Kappler, Daniel, et al.. (2010). Representation of pre-grasp strategies for object manipulation. Figshare. 617–624. 29 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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