From the 1 of 10 linked papers with an AI index.
10 papers
Neural operator learning for collision-aware trajectory planning of spacecraft swarms
Sidhdharth D. Sikka, Suyi Gao, Zehui Lu +2
Autonomous spacecraft swarms must plan fuel-efficient, collision-free maneuvers in increasingly congested orbits, yet classical trajectory optimization scales poorly as pairwise sa…
Accelerating Sampling-Based Control via Learned Linear Koopman Dynamics
Wenjian Hao, Yuxuan Fang, Zehui Lu +1
The paper proposes a model predictive path integral control method that replaces costly nonlinear dynamics with a learned linear deep Koopman operator, enabling faster trajectory s…
Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales
Yang Li, Feng Xue, Fan Mo +6
Deploying robot teams in the real world requires simultaneous adaptation to unseen environments, unknown partners, and varying team sizes, yet existing approaches often address the…
DREAM-Chunk: Reactive Action Chunking with Latent World Model
Wenxi Chen, Kaidi Zhang, Chi Lin +6
Action chunking has become a common interface for vision-language-action (VLA) models, enabling low-frequency policy inference to drive high-frequency robot execution. However, onc…
Efficient Reinforcement Learning using Linear Koopman Dynamics for Nonlinear Robotic Systems
Wenjian Hao, Yuxuan Fang, Zehui Lu +1
This paper presents a model-based reinforcement learning (RL) framework for optimal closed-loop control of nonlinear robotic systems. The proposed approach learns linear lifted dyn…
Online Intention Prediction via Control-Informed Learning
Tianyu Zhou, Zihao Liang, Zehui Lu +1
This paper presents an online intention prediction framework for estimating the goal state of autonomous systems in real time, even when intention is time-varying, and system dynam…