7 citations · 10 across the 4 of their papers we have counts for
4 papers
Grounding Object Relations in Language-Conditioned Robotic Manipulation with Semantic-Spatial Reasoning
Qian Luo, Yunfei Li, Yi Wu
Grounded understanding of natural language in physical scenes can greatly benefit robots that follow human instructions. In object manipulation scenarios, existing end-to-end model…
Benchmarking Augmentation Methods for Learning Robust Navigation Agents: the Winning Entry of the 2021 iGibson Challenge
Naoki Yokoyama, Qian Luo, Dhruv Batra +1
Recent advances in deep reinforcement learning and scalable photorealistic simulation have led to increasingly mature embodied AI for various visual tasks, including navigation. Ho…
A Generalized Robotic Handwriting Learning System based on Dynamic Movement Primitives (DMPs)
Qian Luo, Jing Wu, Matthew Gombolay
Learning from demonstration (LfD) is a powerful learning method to enable a robot to infer how to perform a task given one or more human demonstrations of the desired task. By lear…
A Few Shot Adaptation of Visual Navigation Skills to New Observations using Meta-Learning
Qian Luo, Maks Sorokin, Sehoon Ha
Target-driven visual navigation is a challenging problem that requires a robot to find the goal using only visual inputs. Many researchers have demonstrated promising results using…