76 citations · 116 across the 44 of their papers we have counts for
9 papers · 1 filter
Deadlock-Free Hybrid RL-MAPF Framework for Zero-Shot Multi-Robot Navigation
Haoyi Wang, Licheng Luo, Yiannis Kantaros +2
Multi-robot navigation in cluttered environments presents fundamental challenges in balancing reactive collision avoidance with long-range goal achievement. When navigating through…
CoFineLLM: Conformal Finetuning of LLMs for Language-Instructed Robot Planning
Jun Wang, Yevgeniy Vorobeychik, Yiannis Kantaros
Large Language Models (LLMs) have recently emerged as planners for language-instructed agents, generating sequences of actions to accomplish natural language tasks. However, their…
Conformalized Non-uniform Sampling Strategies for Accelerated Sampling-based Motion Planning
Shubham Natraj, Bruno Sinopoli, Yiannis Kantaros
Sampling-based motion planners (SBMPs) are widely used to compute dynamically feasible robot paths. However, their reliance on uniform sampling often leads to poor efficiency and s…
Safe Planning in Unknown Environments Using Conformalized Semantic Maps
David Smith Sundarsingh, Yifei Li, Tianji Tang +3
This paper addresses semantic planning problems in unknown environments under perceptual uncertainty. The environment contains multiple unknown semantically labeled regions or obje…
NAMO-LLM: Efficient Navigation Among Movable Obstacles with Large Language Model Guidance
Yuqing Zhang, Yiannis Kantaros
Several planners have been proposed to compute robot paths that reach desired goal regions while avoiding obstacles. However, these methods fail when all pathways to the goal are b…
HyperController: A Hyperparameter Controller for Fast and Stable Training of Reinforcement Learning Neural Networks
Jonathan Gornet, Yiannis Kantaros, Bruno Sinopoli
We introduce Hyperparameter Controller (HyperController), a computationally efficient algorithm for hyperparameter optimization during training of reinforcement learning neural net…
Safety Monitoring for Learning-Enabled Cyber-Physical Systems in Out-of-Distribution Scenarios
Vivian Lin, Ramneet Kaur, Yahan Yang +6
The safety of learning-enabled cyber-physical systems is compromised by the well-known vulnerabilities of deep neural networks to out-of-distribution (OOD) inputs. Existing literat…
ConformalNL2LTL: Translating Natural Language Instructions into Temporal Logic Formulas with Conformal Correctness Guarantees
David Smith Sundarsingh, Jun Wang, Jyotirmoy V. Deshmukh +1
Linear Temporal Logic (LTL) is a widely used task specification language for autonomous systems. To mitigate the significant manual effort and expertise required to define LTL-enco…
Learning Vision-Based Neural Network Controllers with Semi-Probabilistic Safety Guarantees
Xinhang Ma, Junlin Wu, Hussein Sibai +2
Ensuring safety in autonomous systems with vision-based control remains a critical challenge due to the high dimensionality of image inputs and the fact that the relationship betwe…