17 citations · 18 across the 5 of their papers we have counts for
5 papers
Local Guidance, Global Impact: Gaussian-Reshaped Trust Region Unlocks Behavior Transitions
Bingxu Liu, Jiashun Liu, Johan Obando-Ceron +5
While Proximal Policy Optimization (PPO) demonstrates strong performance in stationary settings, we show that its standard optimization paradigm struggles in continual and non-stat…
Temporal Logic Guided Motion Primitives for Complex Manipulation Tasks with User Preferences
Hao Wang, Haoyuan He, Weiwei Shang +1
Dynamic movement primitives (DMPs) are a flexible trajectory learning scheme widely used in motion generation of robotic systems. However, existing DMP-based methods mainly focus o…
Gaussian Process Constraint Learning for Scalable Chance-Constrained Motion Planning from Demonstrations
Glen Chou, Hao Wang, Dmitry Berenson
We propose a method for learning constraints represented as Gaussian processes (GPs) from locally-optimal demonstrations. Our approach uses the Karush-Kuhn-Tucker (KKT) optimality…
STRODE: Stochastic Boundary Ordinary Differential Equation
Hengguan Huang, Hongfu Liu, Hao Wang +2
Perception of time from sequentially acquired sensory inputs is rooted in everyday behaviors of individual organisms. Yet, most algorithms for time-series modeling fail to learn dy…
Causal Discovery from Incomplete Data: A Deep Learning Approach
Yuhao Wang, Vlado Menkovski, Hao Wang +2
As systems are getting more autonomous with the development of artificial intelligence, it is important to discover the causal knowledge from observational sensory inputs. By encod…