Papers
23
Total Citations
532
H-Index
11
About
Philipp Schillinger is a robotics researcher whose work sits at the intersection of formal methods, multi-robot systems, and autonomous behavior synthesis. His research focuses primarily on translating high-level mission specifications — expressed in temporal logic — into optimal, executable plans for teams of heterogeneous robots, tackling the deeply challenging problems of task allocation, planning under resource constraints, and human-robot collaboration. Schillinger's most cited contribution, "Simultaneous Task Allocation and Planning for Temporal Logic Goals in Heterogeneous Multi-Robot Systems" (2018, 151 citations), introduced a framework that automatically generates optimal robot behaviors from formal specifications without requiring exhaustive prior enumeration — a significant advance in scalable multi-robot coordination. His early work on human-robot collaborative control, motivated by the DARPA Robotics Challenge, demonstrated these ideas on real humanoid systems in unstructured environments, earning 91 citations and showcasing the practical relevance of formal synthesis methods. Across his portfolio, Schillinger has consistently pushed toward real-world applicability — addressing uncertainty, decentralization, and adaptive collaboration — with contributions spanning probabilistic planning, LTL decomposition, and service robot variability modeling. His work reflects a rare bridge between theoretical rigor and deployable robotic systems, making him a notable voice in autonomous multi-robot planning research.
Research Focus
Key Achievements
Top Papers
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- 4Reactive high-level behavior synthesis for an Atlas humanoid robot44 citations · 2016
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- 6Variability Modeling of Service Robots25 citations · 2019
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