2 citations · 3 across the 8 of their papers we have counts for
10 papers · 1 filter
Learning Causal Structure Distributions for Robust Planning
Alejandro Murillo-Gonzalez, Junhong Xu, Lantao Liu
Structural causal models describe how the components of a robotic system interact. They provide both structural and functional information about the relationships that are present…
ADEPT: Adaptive Diffusion Environment for Policy Transfer Sim-to-Real
Youwei Yu, Junhong Xu, Lantao Liu
Model-free reinforcement learning has emerged as a powerful method for developing robust robot control policies capable of navigating through complex and unstructured environments.…
Adaptive Diffusion Terrain Generator for Autonomous Uneven Terrain Navigation
Youwei Yu, Junhong Xu, Lantao Liu
Model-free reinforcement learning has emerged as a powerful method for developing robust robot control policies capable of navigating through complex and unstructured terrains. The…
Context-Generative Default Policy for Bounded Rational Agent
Durgakant Pushp, Junhong Xu, Zheng Chen +1
Bounded rational agents often make decisions by evaluating a finite selection of choices, typically derived from a reference point termed the default policy,' based on previous…
Causal Inference for De-biasing Motion Estimation from Robotic Observational Data
Junhong Xu, Kai Yin, Jason M. Gregory +1
Robot data collected in complex real-world scenarios are often biased due to safety concerns, human preferences, and mission or platform constraints. Consequently, robot learning f…
Decision-Making Among Bounded Rational Agents
Junhong Xu, Durgakant Pushp, Kai Yin +1
When robots share the same workspace with other intelligent agents (e.g., other robots or humans), they must be able to reason about the behaviors of their neighboring agents while…