10 citations · 25 across the 4 of their papers we have counts for
7 papers · 1 filter
Hyperparameter Auto-tuning in Self-Supervised Robotic Learning
Jiancong Huang, Juan Rojas, Matthieu Zimmer +3
Policy optimization in reinforcement learning requires the selection of numerous hyperparameters across different environments. Fixing them incorrectly may negatively impact optimi…
Invariant Transform Experience Replay: Data Augmentation for Deep Reinforcement Learning
Yijiong Lin, Jiancong Huang, Matthieu Zimmer +3
Deep Reinforcement Learning (RL) is a promising approach for adaptive robot control, but its current application to robotics is currently hindered by high sample requirements. To a…
Endowing Robots with Longer-term Autonomy by Recovering from External Disturbances in Manipulation through Grounded Anomaly Classification and Recovery Policies
Hongmin Wu, Shuangqi Luo, Longxin Chen +5
Robot manipulation is increasingly poised to interact with humans in co-shared workspaces. Despite increasingly robust manipulation and control algorithms, failure modes continue t…
Dynamic Interaction Probabilistic Movement Primitives
Shuangda Duan, Longxin Chen, Hongmin Wu +3
Human-robot collaboration is on the rise. Robots need to increasingly improve the efficiency and smoothness with which they assist humans by properly anticipating a human's intenti…
Learning Human-Robot Collaboration Insights through the Integration of Muscle Activity in Interaction Motion Models
Longxin Chen, Juan Rojas, Shuangda Duan +1
Recent progress in human-robot collaboration makes fast and fluid interactions possible, even when human observations are partial and occluded. Methods like Interaction Probabilist…
Robot Introspection with Bayesian Nonparametric Vector Autoregressive Hidden Markov Models
Hongmin Wu, Hongbin Lin, Yisheng Guan +2
Robot introspection, as opposed to anomaly detection typical in process monitoring, helps a robot understand what it is doing at all times. A robot should be able to identify its a…