Philipp Schillinger

535 total citations
20 papers, 323 citations indexed

About

Philipp Schillinger is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Philipp Schillinger has authored 20 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 12 papers in Control and Systems Engineering and 7 papers in Computational Theory and Mathematics. Recurrent topics in Philipp Schillinger's work include Robot Manipulation and Learning (10 papers), Formal Methods in Verification (7 papers) and Reinforcement Learning in Robotics (6 papers). Philipp Schillinger is often cited by papers focused on Robot Manipulation and Learning (10 papers), Formal Methods in Verification (7 papers) and Reinforcement Learning in Robotics (6 papers). Philipp Schillinger collaborates with scholars based in Germany, Sweden and United States. Philipp Schillinger's co-authors include Dimos V. Dimarogonas, Mathias Bürger, Oskar von Stryk, Stefan Kohlbrecher, David C. Conner, Hadas Kress‐Gazit, Vitchyr H. Pong, Patrizio Pelliccione, Davide Brugali and Thorsten Berger and has published in prestigious journals such as The International Journal of Robotics Research, Robotics and Autonomous Systems and Robotics and Computer-Integrated Manufacturing.

In The Last Decade

Philipp Schillinger

20 papers receiving 317 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Philipp Schillinger Germany 9 125 118 104 80 79 20 323
Bruno Lacerda United Kingdom 13 190 1.5× 122 1.0× 147 1.4× 53 0.7× 61 0.8× 41 386
Martijn Rooker Austria 7 56 0.4× 71 0.6× 52 0.5× 128 1.6× 51 0.6× 29 346
F. Kabanza Canada 11 213 1.7× 70 0.6× 130 1.3× 120 1.5× 64 0.8× 15 400
Alphan Ulusoy United States 10 144 1.2× 124 1.1× 190 1.8× 155 1.9× 102 1.3× 18 417
Tiago Vaquero United States 10 146 1.2× 61 0.5× 22 0.2× 109 1.4× 49 0.6× 38 316
V. A. Ziparo Italy 8 84 0.7× 112 0.9× 52 0.5× 106 1.3× 68 0.9× 25 333
Anders Orebäck Sweden 5 108 0.9× 111 0.9× 17 0.2× 44 0.6× 129 1.6× 6 286
Geoffrey Biggs Japan 7 74 0.6× 52 0.4× 17 0.2× 35 0.4× 138 1.7× 29 282
Yash Vardhan Pant United States 7 90 0.7× 58 0.5× 113 1.1× 46 0.6× 86 1.1× 31 278
P. Freedman Canada 11 70 0.6× 85 0.7× 112 1.1× 65 0.8× 64 0.8× 29 378

Countries citing papers authored by Philipp Schillinger

Since Specialization
Citations

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

Fields of papers citing papers by Philipp Schillinger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philipp Schillinger

This figure shows the co-authorship network connecting the top 25 collaborators of Philipp Schillinger. A scholar is included among the top collaborators of Philipp Schillinger 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 Philipp Schillinger. Philipp Schillinger 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.
Schillinger, Philipp, et al.. (2024). Uncertainty-driven Exploration Strategies for Online Grasp Learning. 781–787. 2 indexed citations
2.
Yu, Zehao, Miroslav Gabriel, Philipp Schillinger, et al.. (2024). Efficient End-to-End Detection of 6-DoF Grasps for Robotic Bin Picking. 5427–5433. 2 indexed citations
3.
Le, Huy Viet, et al.. (2024). Pseudo Labeling and Contextual Curriculum Learning for Online Grasp Learning in Robotic Bin Picking. abs/2305.03942. 788–794. 1 indexed citations
4.
Rozo, Leonel, Philipp Schillinger, Meng Guo, et al.. (2023). The e-Bike motor assembly: Towards advanced robotic manipulation for flexible manufacturing. Robotics and Computer-Integrated Manufacturing. 85. 102637–102637. 5 indexed citations
5.
Schillinger, Philipp, et al.. (2023). Model-Free Grasping with Multi-Suction Cup Grippers for Robotic Bin Picking. 3107–3113. 5 indexed citations
6.
Conner, David C., et al.. (2022). ROS 2-Based Flexible Behavior Engine for Flexible Navigation. 674–681. 3 indexed citations
7.
Schillinger, Philipp, et al.. (2022). Optimizing Demonstrated Robot Manipulation Skills for Temporal Logic Constraints. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 133. 1255–1262. 4 indexed citations
8.
Karras, George C., Christos K. Verginis, Alexandros Makris, et al.. (2021). Efficient Cooperation of Heterogeneous Robotic Agents: A Decentralized Framework. IEEE Robotics & Automation Magazine. 28(2). 74–87. 6 indexed citations
9.
Schillinger, Philipp, Alexandros Makris, Wei Ren, et al.. (2021). Adaptive heterogeneous multi-robot collaboration from formal task specifications. Robotics and Autonomous Systems. 145. 103866–103866. 8 indexed citations
10.
Schillinger, Philipp, Mathias Bürger, & Dimos V. Dimarogonas. (2019). Hierarchical LTL-Task MDPs for Multi-Agent Coordination through Auctioning and Learning. The International Journal of Robotics Research. 10 indexed citations
11.
Strüber, Daniel, et al.. (2019). Variability Modeling of Service Robots. Aisberg (University of Bergamo). 1–6. 21 indexed citations
12.
Schillinger, Philipp, et al.. (2018). On the Design of Penalty Structures for Minimum-Violation LTL Motion Planning. 4153–4158. 3 indexed citations
13.
Schillinger, Philipp, Mathias Bürger, & Dimos V. Dimarogonas. (2018). Auctioning over Probabilistic Options for Temporal Logic-Based Multi-Robot Cooperation Under Uncertainty. KTH Publication Database DiVA (KTH Royal Institute of Technology). 7330–7337. 11 indexed citations
14.
Schillinger, Philipp, et al.. (2018). Improving Multi-Robot Behavior Using Learning-Based Receding Horizon Task Allocation. KTH Publication Database DiVA (KTH Royal Institute of Technology). 7 indexed citations
15.
Schillinger, Philipp, Mathias Bürger, & Dimos V. Dimarogonas. (2018). Simultaneous task allocation and planning for temporal logic goals in heterogeneous multi-robot systems. The International Journal of Robotics Research. 37(7). 818–838. 103 indexed citations
16.
Schillinger, Philipp, Mathias Bürger, & Dimos V. Dimarogonas. (2017). Multi-objective search for optimal multi-robot planning with finite LTL specifications and resource constraints. KTH Publication Database DiVA (KTH Royal Institute of Technology). 768–774. 14 indexed citations
17.
Schillinger, Philipp, Stefan Kohlbrecher, & Oskar von Stryk. (2016). Human-robot collaborative high-level control with application to rescue robotics. 2796–2802. 64 indexed citations
18.
Kohlbrecher, Stefan, et al.. (2016). A Comprehensive Software Framework for Complex Locomotion and Manipulation Tasks Applicable to Different Types of Humanoid Robots. Frontiers in Robotics and AI. 3. 8 indexed citations
19.
Schillinger, Philipp, et al.. (2016). Reactive high-level behavior synthesis for an Atlas humanoid robot. 4192–4199. 25 indexed citations
20.
Kohlbrecher, Stefan, et al.. (2016). Collaborative Autonomy between High‐level Behaviors and Human Operators for Remote Manipulation Tasks using Different Humanoid Robots. Journal of Field Robotics. 34(2). 333–358. 21 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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