1 citations · 1 across the 9 of their papers we have counts for
11 papers
Active Generative Simulation: Meta-Learning What to Simulate for Sim-and-Real Policy Co-Training
Liqian Ma, Vaibhav Saxena, Utkarsh Aashu Mishra +3
Sim-and-real co-training is an effective way to scale robot learning by augmenting limited real-world demonstrations with simulation data. However, existing approaches typically tr…
ACWM-Phys: Investigating Generalized Physical Interaction in Action-Conditioned Video World Models
Haotian Xue, Yipu Chen, Liqian Ma +4
Action-conditioned world models (ACWMs) have shown strong promise for video prediction and decision-making. However, existing benchmarks are largely restricted to egocentric naviga…
Feedback Motion Planning for Stochastic Nonlinear Systems with Signal Temporal Logic Specifications
Liqian Ma, Zishun Liu, Glen Chou +1
We study feedback motion planning for continuous-time stochastic nonlinear systems under signal temporal logic (STL) specifications. We propose a framework that synthesizes control…
Concentration of Stochastic System Trajectories with Time-varying Contraction Conditions
Zishun Liu, Liqian Ma, Hongzhe Yu +1
We establish two concentration inequalities for nonlinear stochastic system under time-varying contraction conditions. The key to our approach is an energy function termed Averaged…
Generalizable Domain Adaptation for Sim-and-Real Policy Co-Training
Shuo Cheng, Liqian Ma, Zhenyang Chen +3
Behavior cloning has shown promise for robot manipulation, but real-world demonstrations are costly to acquire at scale. While simulated data offers a scalable alternative, particu…
Model Predictive Control with High-Probability Safety Guarantee for Nonlinear Stochastic Systems
Zishun Liu, Liqian Ma, Yongxin Chen
We present a model predictive control (MPC) framework for nonlinear stochastic systems that ensures safety guarantee with high probability. Unlike most existing stochastic MPC sche…
Trajectory Optimization of Stochastic Systems under Chance Constraints via Set Erosion
Zishun Liu, Liqian Ma, Yongxin Chen
We study the trajectory optimization problem under chance constraints for continuous-time stochastic systems. To address chance constraints imposed on the entire stochastic traject…
Safety Verification of Stochastic Systems under Signal Temporal Logic Specifications
Liqian Ma, Zishun Liu, Hongzhe Yu +1
We study the verification problem of stochastic systems under signal temporal logic (STL) specifications. We propose a novel approach that enables the verification of the probabili…
DexSim2Real: Building Explicit World Model for Precise Articulated Object Dexterous Manipulation
Taoran Jiang, Yixuan Guan, Liqian Ma +7
Articulated objects are ubiquitous in daily life. In this paper, we present DexSim2Real, a novel framework for goal-conditioned articulated object manipulation. The core of o…
Meta-Control: Automatic Model-based Control Synthesis for Heterogeneous Robot Skills
Tianhao Wei, Liqian Ma, Rui Chen +2
The requirements for real-world manipulation tasks are diverse and often conflicting; some tasks require precise motion while others require force compliance; some tasks require av…
Robust Safe Control with Multi-Modal Uncertainty
Tianhao Wei, Liqian Ma, Ravi Pandya +1
Safety in dynamic systems with prevalent uncertainties is crucial. Current robust safe controllers, designed primarily for uni-modal uncertainties, may be either overly conservativ…