activity
20132026
most citedOvercoming Exploration: Deep Reinforcement Learning for Continuous Control in Cluttered Environments from Temporal Logic Specifications

32 citations · 88 across the 33 of their papers we have counts for

collaborators

37 papers

eess.SY2026

Expressive Power of WSTL Formulas for Learning to Rank

Ruya Karagulle, Gustavo A. Cardona, Necmiye Ozay +1

Weighted Signal Temporal Logic (WSTL) is increasingly used as a scoring function in learning-to-rank problems of trajectories with safety guarantees, where its weighted quantitativ…

cs.RO2026

Differentiable SpaTiaL: Symbolic Learning and Reasoning with Geometric Temporal Logic for Manipulation Tasks

Licheng Luo, Kaier Liang, Cristian-Ioan Vasile +1

Executing complex manipulation in cluttered environments requires satisfying coupled geometric and temporal constraints. Although Spatio-Temporal Logic (SpaTiaL) offers a principle…

cs.RO2025

A*-based Temporal Logic Path Planning with User Preferences on Relaxed Task Satisfaction

Disha Kamale, Xi Yu, Cristian-Ioan Vasile

In this work, we consider the problem of planning for temporal logic tasks in large robot environments. When full task compliance is unattainable, we aim to achieve the best possib…

cs.RO2025

Safe and Optimal Learning from Preferences via Weighted Temporal Logic with Applications in Robotics and Formula 1

Ruya Karagulle, Cristian-Ioan Vasile, Necmiye Ozay

Autonomous systems increasingly rely on human feedback to align their behavior, expressed as pairwise comparisons, rankings, or demonstrations. While existing methods can adapt beh…

cs.RO2025

An Iterative Approach for Heterogeneous Multi-Agent Route Planning with Resource Transportation Uncertainty and Temporal Logic Goals

Gustavo A. Cardona, Kaier Liang, Cristian-Ioan Vasile

This paper presents an iterative approach for heterogeneous multi-agent route planning in environments with unknown resource distributions. We focus on a team of robots with divers…

cs.RO2025

Safe Navigation in Dynamic Environments Using Data-Driven Koopman Operators and Conformal Prediction

Kaier Liang, Guang Yang, Mingyu Cai +1

We propose a novel framework for safe navigation in dynamic environments by integrating Koopman operator theory with conformal prediction. Our approach leverages data-driven Koopma…