6 papers
Plug-and-Play Reweighting for Resilient Collaborative Decision-Making in Connected Autonomous Driving
Jiewen Liu, Rui Liu, Matthew Lee +3
Collaborative decision-making is a fundamental capability in multi-robot systems, such as connected autonomous vehicles. However, perceptual noise and adversarial attacks in collab…
Collaborative Planning with Concurrent Synchronization for Operationally Constrained UAV-UGV Teams
Zihao Deng, Qianhuang Li, Peng Gao +4
Collaborative planning under operational constraints is an essential capability for heterogeneous robot teams tackling complex large-scale real-world tasks. Unmanned Aerial Vehicle…
MMCD: Multi-Modal Collaborative Decision-Making for Connected Autonomy with Knowledge Distillation
Rui Liu, Zikang Wang, Peng Gao +3
Autonomous systems have advanced significantly, but challenges persist in accident-prone environments where robust decision-making is crucial. A single vehicle's limited sensor ran…
CAML: Collaborative Auxiliary Modality Learning for Multi-Agent Systems
Rui Liu, Yu Shen, Peng Gao +2
Multi-modal learning has emerged as a key technique for improving performance across domains such as autonomous driving, robotics, and reasoning. However, in certain scenarios, par…
Adaptive Conformal Guidance for Learning under Uncertainty
Rui Liu, Peng Gao, Yu Shen +2
Learning with guidance has proven effective across a wide range of machine learning systems. Guidance may, for example, come from annotated datasets in supervised learning, pseudo-…
Collaborative Decision-Making Using Spatiotemporal Graphs in Connected Autonomy
Peng Gao, Yu Shen, Ming C. Lin
Collaborative decision-making is an essential capability for multi-robot systems, such as connected vehicles, to collaboratively control autonomous vehicles in accident-prone scena…