17 citations · 20 across the 8 of their papers we have counts for
9 papers
LEARN: Learning End-to-End Aerial Resource-Constrained Multi-Robot Navigation
Darren Chiu, Zhehui Huang, Ruohai Ge +1
Nano-UAV teams offer great agility yet face severe navigation challenges due to constrained onboard sensing, communication, and computation. Existing approaches rely on high-resolu…
Latent Activation Editing: Inference-Time Refinement of Learned Policies for Safer Multirobot Navigation
Satyajeet Das, Darren Chiu, Zhehui Huang +2
Reinforcement learning has enabled significant progress in complex domains such as coordinating and navigating multiple quadrotors. However, even well-trained policies remain vulne…
Compositional Coordination for Multi-Robot Teams with Large Language Models
Zhehui Huang, Guangyao Shi, Yuwei Wu +2
Multi-robot coordination has traditionally relied on a mission-specific and expert-driven pipeline, where natural language mission descriptions are manually translated by domain ex…
Can Large Language Models Solve Robot Routing?
Zhehui Huang, Guangyao Shi, Gaurav S. Sukhatme
Routing problems are common in mobile robotics, encompassing tasks such as inspection, surveillance, and coverage. Depending on the objective and constraints, these problems often…
Guaranteed Trust Region Optimization via Two-Phase KL Penalization
K. R. Zentner, Ujjwal Puri, Zhehui Huang +1
On-policy reinforcement learning (RL) has become a popular framework for solving sequential decision problems due to its computational efficiency and theoretical simplicity. Some o…
HyperPPO: A scalable method for finding small policies for robotic control
Shashank Hegde, Zhehui Huang, Gaurav S. Sukhatme
Models with fewer parameters are necessary for the neural control of memory-limited, performant robots. Finding these smaller neural network architectures can be time-consuming. We…