3 citations · 8 across the 15 of their papers we have counts for
7 papers · 1 filter
PointMapPolicy: Structured Point Cloud Processing for Multi-Modal Imitation Learning
Xiaogang Jia, Qian Wang, Anrui Wang +12
Robotic manipulation systems benefit from complementary sensing modalities, where each provides unique environmental information. Point clouds capture detailed geometric structure,…
MoRe-ERL: Learning Motion Residuals using Episodic Reinforcement Learning
Xi Huang, Hongyi Zhou, Ge Li +5
We propose MoRe-ERL, a framework that combines Episodic Reinforcement Learning (ERL) and residual learning, which refines preplanned reference trajectories into safe, feasible, and…
BEAST: Efficient Tokenization of B-Splines Encoded Action Sequences for Imitation Learning
Hongyi Zhou, Weiran Liao, Xi Huang +11
We present the B-spline Encoded Action Sequence Tokenizer (BEAST), a novel action tokenizer that encodes action sequences into compact discrete or continuous tokens using B-splines…
Chunking the Critic: A Transformer-based Soft Actor-Critic with N-Step Returns
Dong Tian, Onur Celik, Gerhard Neumann
We introduce a sequence-conditioned critic for Soft Actor-Critic (SAC) that models trajectory context with a lightweight Transformer and trains on aggregated -step targets. Unli…
Towards Fusing Point Cloud and Visual Representations for Imitation Learning
Atalay Donat, Xiaogang Jia, Xi Huang +7
Learning for manipulation requires using policies that have access to rich sensory information such as point clouds or RGB images. Point clouds efficiently capture geometric struct…
IRIS: An Immersive Robot Interaction System
Xinkai Jiang, Qihao Yuan, Enes Ulas Dincer +11
This paper introduces IRIS, an Immersive Robot Interaction System leveraging Extended Reality (XR). Existing XR-based systems enable efficient data collection but are often challen…
DIME:Diffusion-Based Maximum Entropy Reinforcement Learning
Onur Celik, Zechu Li, Denis Blessing +5
Maximum entropy reinforcement learning (MaxEnt-RL) has become the standard approach to RL due to its beneficial exploration properties. Traditionally, policies are parameterized us…