14 citations · 32 across the 10 of their papers we have counts for
11 papers
Robot Tactile Gesture Recognition Based on Full-body Modular E-skin
Shuo Jiang, Boce Hu, Linfeng Zhao +1
With the development of robot electronic skin technology, various tactile sensors, enhanced by AI, are unlocking a new dimension of perception for robots. In this work, we explore…
Equivariant Action Sampling for Reinforcement Learning and Planning
Linfeng Zhao, Owen Howell, Xupeng Zhu +4
Reinforcement learning (RL) algorithms for continuous control tasks require accurate sampling-based action selection. Many tasks, such as robotic manipulation, contain inherent pro…
Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps
Linfeng Zhao, Lawson L. S. Wong
Learning navigation capabilities in different environments has long been one of the major challenges in decision-making. In this work, we focus on zero-shot navigation ability usin…
E(2)-Equivariant Graph Planning for Navigation
Linfeng Zhao, Hongyu Li, Taskin Padir +2
Learning for robot navigation presents a critical and challenging task. The scarcity and costliness of real-world datasets necessitate efficient learning approaches. In this letter…
Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning?
Linfeng Zhao, Owen Howell, Jung Yeon Park +3
In robotic tasks, changes in reference frames typically do not influence the underlying physical properties of the system, which has been known as invariance of physical laws.These…
Equivariant Single View Pose Prediction Via Induced and Restricted Representations
Owen Howell, David Klee, Ondrej Biza +2
Learning about the three-dimensional world from two-dimensional images is a fundamental problem in computer vision. An ideal neural network architecture for such tasks would levera…
Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation
Linfeng Zhao, Huazhe Xu, Lawson L. S. Wong
Differentiable planning promises end-to-end differentiability and adaptivity. However, an issue prevents it from scaling up to larger-scale problems: they need to differentiate thr…
Integrating Symmetry into Differentiable Planning with Steerable Convolutions
Linfeng Zhao, Xupeng Zhu, Lingzhi Kong +2
We study how group symmetry helps improve data efficiency and generalization for end-to-end differentiable planning algorithms when symmetry appears in decision-making tasks. Motiv…
Toward Compositional Generalization in Object-Oriented World Modeling
Linfeng Zhao, Lingzhi Kong, Robin Walters +1
Compositional generalization is a critical ability in learning and decision-making. We focus on the setting of reinforcement learning in object-oriented environments to study compo…
Learning Symmetric Embeddings for Equivariant World Models
Jung Yeon Park, Ondrej Biza, Linfeng Zhao +2
Incorporating symmetries can lead to highly data-efficient and generalizable models by defining equivalence classes of data samples related by transformations. However, characteriz…
Deep Imitation Learning for Bimanual Robotic Manipulation
Fan Xie, Alexander Chowdhury, M. Clara De Paolis Kaluza +3
We present a deep imitation learning framework for robotic bimanual manipulation in a continuous state-action space. A core challenge is to generalize the manipulation skills to ob…