8 citations · 13 across the 16 of their papers we have counts for
20 papers
Data-Driven Spiking Control for Distributed -Nash Equilibrium Seeking
Linqi Wang, Wei Xiao, Yuzhou Wei +3
This paper studies how a feedback law synthesized directly from data can be realized by spiking control while retaining a game-theoretic performance guarantee. We consider distribu…
FlowPilot: Real-Time World-Action Modeling for Agile UAV Navigation
Runqing Wang, Ding Yu, Pengyuan Min +6
We present FlowPilot, a compact world-action model for real-time onboard UAV navigation from depth. Unlike map-then-optimize pipelines that require local reconstruction or end-to-e…
AeroAct: Action-Centered World-Action Models for Language-Conditioned Quadrotor Flight
Xinhong Zhang, Qiyuan Zhu, Yubo Huang +8
Language-conditioned quadrotor flight requires a policy to ground semantic goals, anticipate the visual consequences of ego-motion, and output control references that remain smooth…
Data-driven Kernel-based Predictive Control with Stability and Robustness Guarantees
Wenjie Liu, Yifei Li, Gang Wang +1
In this paper, we provide a theoretical analysis of the closed-loop properties of a data-driven kernel-based predictive control (DDKPC) scheme developed solely from input-output da…
Data-Driven Robust MPC for Unknown Nonlinear Systems via Set-Membership Learning
Yuzhou Wei, Wenjie Liu, Yifan Xie +3
Data-driven model predictive control (MPC) has become an attractive approach for controlling unknown systems, especially when data are corrupted by noise. However, most existing da…
Robust Data-Driven Nash Equilibrium Seeking under Partial-Decision Information
Linqi Wang, Yifei Li, Wenjie Liu +3
This paper presents a data-driven framework for decentralized Nash equilibrium (NE) seeking in multi-agent systems with unknown linear dynamics subject to exogenous disturbances, o…
MAD: Mapping-Aware World Models for Agile Quadrotor Flight
Xinhong Zhang, Runqing Wang, Yunfan Ren +6
Agile quadrotor flight in cluttered scenes requires more than a reactive mapping from a depth image to a control command: the vehicle must remember which regions have been observed…
Data-driven control of network systems: Accounting for communication adaptivity and security
Gang Wang, Wenjie Liu, Yifei Li +3
Over the past decades, network systems have surged in significance, driven by merging technological advancements. These systems play pivotal roles in diverse applications ranging f…
DiffAero: A GPU-Accelerated Differentiable Simulation Framework for Efficient Quadrotor Policy Learning
Xinhong Zhang, Runqing Wang, Yunfan Ren +4
This letter introduces DiffAero, a lightweight, GPU-accelerated, and fully differentiable simulation framework designed for efficient quadrotor control policy learning. DiffAero su…
SPGrasp: Spatiotemporal Prompt-driven Grasp Synthesis in Dynamic Scenes
Yunpeng Mei, Hongjie Cao, Yinqiu Xia +4
Real-time interactive grasp synthesis for dynamic objects remains challenging as existing methods fail to achieve low-latency inference while maintaining promptability. To bridge t…
Multi-agent Embodied AI: Advances and Future Directions
Zhaohan Feng, Ruiqi Xue, Lei Yuan +7
Embodied artificial intelligence (Embodied AI) plays a pivotal role in the application of advanced technologies in the intelligent era, where AI systems are integrated with physica…
Data-driven Internal Model Control for Output Regulation
Wenjie Liu, Yifei Li, Jian Sun +4
Output regulation is a fundamental problem in control theory, extensively studied since the 1970s. Traditionally, research has primarily addressed scenarios where the system model…
Robust Offline Imitation Learning Through State-level Trajectory Stitching
Shuze Wang, Yunpeng Mei, Hongjie Cao +4
Imitation learning (IL) has proven effective for enabling robots to acquire visuomotor skills through expert demonstrations. However, traditional IL methods are limited by their re…
Time-optimal Flight in Cluttered Environments via Safe Reinforcement Learning
Wei Xiao, Zhaohan Feng, Ziyu Zhou +3
This paper addresses the problem of guiding a quadrotor through a predefined sequence of waypoints in cluttered environments, aiming to minimize the flight time while avoiding coll…
Learning Hybrid Policies for MPC with Application to Drone Flight in Unknown Dynamic Environments
Zhaohan Feng, Jie Chen, Wei Xiao +3
In recent years, drones have found increased applications in a wide array of real-world tasks. Model predictive control (MPC) has emerged as a practical method for drone flight con…
Distributed Data-driven Unknown-input Observers for State Estimation
Yuzhou Wei, Giorgia Disarò, Wenjie Liu +3
Unknown inputs related to, e.g., sensor aging, modeling errors, or device bias, represent a major concern in wireless sensor networks, as they degrade the state estimation performa…
Robust Control of Unknown Switched Linear Systems from Noisy Data
Wenjie Liu, Yifei Li, Jian Sun +2
This paper investigates the problem of data-driven stabilization for linear discrete-time switched systems with unknown switching dynamics. In the absence of noise, a data-based st…
Data-driven Control Against False Data Injection Attacks
Wenjie Liu, Lidong Li, Jian Sun +3
The rise of cyber-security concerns has brought significant attention to the analysis and design of cyber-physical systems (CPSs). Among the various types of cyberattacks, denial-o…
Self-triggered Consensus Control of Multi-agent Systems from Data
Yifei Li, Xin Wang, Jian Sun +2
This paper considers self-triggered consensus control of unknown linear multi-agent systems (MASs). Self-triggering mechanisms (STMs) are widely used in MASs, thanks to their advan…
STORM: Efficient Stochastic Transformer based World Models for Reinforcement Learning
Weipu Zhang, Gang Wang, Jian Sun +2
Recently, model-based reinforcement learning algorithms have demonstrated remarkable efficacy in visual input environments. These approaches begin by constructing a parameterized s…