21 citations · 129 across the 42 of their papers we have counts for
6 papers · 1 filter
Temporally Robust Multi-Agent STL Motion Planning in Continuous Time
Joris Verhagen, Lars Lindemann, Jana Tumova
Signal Temporal Logic (STL) is a formal language over continuous-time signals (such as trajectories of a multi-agent system) that allows for the specification of complex spatial an…
Conformal Predictive Safety Filter for RL Controllers in Dynamic Environments
Kegan J. Strawn, Nora Ayanian, Lars Lindemann
The interest in using reinforcement learning (RL) controllers in safety-critical applications such as robot navigation around pedestrians motivates the development of additional sa…
Physics Constrained Motion Prediction with Uncertainty Quantification
Renukanandan Tumu, Lars Lindemann, Truong Nghiem +1
Predicting the motion of dynamic agents is a critical task for guaranteeing the safety of autonomous systems. A particular challenge is that motion prediction algorithms should obe…
Adaptive Conformal Prediction for Motion Planning among Dynamic Agents
Anushri Dixit, Lars Lindemann, Skylar Wei +3
This paper proposes an algorithm for motion planning among dynamic agents using adaptive conformal prediction. We consider a deterministic control system and use trajectory predict…
Safe Planning in Dynamic Environments using Conformal Prediction
Lars Lindemann, Matthew Cleaveland, Gihyun Shim +1
We propose a framework for planning in unknown dynamic environments with probabilistic safety guarantees using conformal prediction. Particularly, we design a model predictive cont…
Robust Motion Planning in the Presence of Estimation Uncertainty
Lars Lindemann, Matthew Cleaveland, Yiannis Kantaros +1
Motion planning is a fundamental problem and focuses on finding control inputs that enable a robot to reach a goal region while safely avoiding obstacles. However, in many situatio…