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20242026
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cs.RO2026

Distributed Model-Based Diffusion For Scalable Multi-Robot Trajectory Optimization

Haejoon Lee, Xinyi Wang, Taekyung Kim +1

Trajectory optimization for multi-robot systems remains a critical challenge, particularly when navigating highly non-convex, non-linear, and non-differentiable environments. While…

cs.RO2026

Stochastic Multi-Objective Kinodynamic Planning Against Adversaries

Thomas Marshall Vielmetti, Daniel Cherenson, Dimitra Panagou

This paper addresses multi-objective kinodynamic planning in environments with stochastic hybrid adversaries that probabilistically transition to adversarial modes based on the ego…

cs.RO2026

SEAMLiS: Visibility-Aware Safety for Perception-Limited Multi-Robot Exploration

Taekyung Kim, Rahul H Kumar, Aswin D. Menon +2

Autonomous exploration in unknown environments is typically driven by informative frontiers, viewpoints, or trajectories, while local safety controllers avoid obstacles represented…

cs.RO2026

Learning to Adapt Control Barrier Functions Under Epistemic and Aleatoric Uncertainty

Taekyung Kim, Robin Inho Kee, Dimitra Panagou

Control barrier functions (CBFs) provide a tractable mechanism for enforcing safety constraints in robotic systems, but their practical performance depends strongly on the choice o…

cs.RO2026

A Formal gatekeeper Framework for Safe Dual Control with Active Exploration

Kaleb Ben Naveed, Devansh R. Agrawal, Dimitra Panagou

Planning safe trajectories under model uncertainty is a fundamental challenge. Robust planning ensures safety by considering worst-case realizations, yet ignores uncertainty reduct…

cs.RO2026

Reinforcement Learning for Risk Adaptation via Differentiable CVaR Barrier Functions

Xinyi Wang, Taekyung Kim, Bardh Hoxha +2

Planning through crowded environments under uncertain obstacle motions remains difficult, as stochastic interactions often induce overly conservative behavior or reduced efficiency…