3 citations · 7 across the 19 of their papers we have counts for
6 papers · 1 filter
Learning Predictive Safety Filter via Decomposition of Robust Invariant Set
Zeyang Li, Chuxiong Hu, Weiye Zhao +1
Ensuring safety of nonlinear systems under model uncertainty and external disturbances is crucial, especially for real-world control tasks. Predictive methods such as robust model…
Synthesis and verification of robust-adaptive safe controllers
Simin Liu, Kai S. Yun, John M. Dolan +1
Safe control with guarantees generally requires the system model to be known. It is far more challenging to handle systems with uncertain parameters. In this paper, we propose a ge…
Absolute Policy Optimization
Weiye Zhao, Feihan Li, Yifan Sun +3
In recent years, trust region on-policy reinforcement learning has achieved impressive results in addressing complex control tasks and gaming scenarios. However, contemporary state…
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…
Simulation-aided Learning from Demonstration for Robotic LEGO Construction
Ruixuan Liu, Alan Chen, Xusheng Luo +1
Recent advancements in manufacturing have a growing demand for fast, automatic prototyping (i.e. assembly and disassembly) capabilities to meet users' needs. This paper studies aut…
A Lightweight and Transferable Design for Robust LEGO Manipulation
Ruixuan Liu, Yifan Sun, Changliu Liu
Lego is a well-known platform for prototyping pixelized objects. However, robotic Lego prototyping (i.e., manipulating Lego bricks) is challenging due to the tight connections and…