Papers
13
Total Citations
576
H-Index
7
About
Lars Lindemann is a prominent researcher at the intersection of formal methods, control theory, and robotics, with a particular focus on Signal Temporal Logic (STL) as a framework for specifying and enforcing complex behavioral requirements in autonomous and multi-robot systems. His most influential contribution, "Control Barrier Functions for Signal Temporal Logic Tasks" (2018, 307 citations), introduced a computationally efficient approach that made temporal logic-based control practically scalable — a long-standing challenge in the field. Building on this foundation, Lindemann extended his work to collaborative multi-agent settings, addressing how distributed robotic teams can satisfy coupled temporal logic tasks in real time. His research into robustness — including spatial, temporal, and asynchronous dimensions of STL — has significantly advanced the resilience of safety-critical autonomous systems against uncertainty and timing perturbations. More recently, he has broadened his scope to include risk-aware robotics, conformal prediction-based safety filters for reinforcement learning controllers, and reactive planning for human-robot interaction. With a growing body of work spanning theoretical foundations and experimental validation, Lindemann's research has established him as a key contributor to the formal synthesis and verification of safe, intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Control Barrier Functions for Signal Temporal Logic Tasks307 citations · 2018
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- 4Prescribed performance control for signal temporal logic specifications51 citations · 2017
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