24 citations · 116 across the 50 of their papers we have counts for
50 papers
Bisimulation metric for Model Predictive Control
Yutaka Shimizu, Masayoshi Tomizuka
Model-based reinforcement learning has shown promise for improving sample efficiency and decision-making in complex environments. However, existing methods face challenges in train…
TrajSSL: Trajectory-Enhanced Semi-Supervised 3D Object Detection
Philip Jacobson, Yichen Xie, Mingyu Ding +4
Semi-supervised 3D object detection is a common strategy employed to circumvent the challenge of manually labeling large-scale autonomous driving perception datasets. Pseudo-labeli…
Embodiment-Agnostic Action Planning via Object-Part Scene Flow
Weiliang Tang, Jia-Hui Pan, Wei Zhan +6
Observing that the key for robotic action planning is to understand the target-object motion when its associated part is manipulated by the end effector, we propose to generate the…
RoVi-Aug: Robot and Viewpoint Augmentation for Cross-Embodiment Robot Learning
Lawrence Yunliang Chen, Chenfeng Xu, Karthik Dharmarajan +6
Scaling up robot learning requires large and diverse datasets, and how to efficiently reuse collected data and transfer policies to new embodiments remains an open question. Emergi…
DSLO: Deep Sequence LiDAR Odometry Based on Inconsistent Spatio-temporal Propagation
Huixin Zhang, Guangming Wang, Xinrui Wu +5
This paper introduces a 3D point cloud sequence learning model based on inconsistent spatio-temporal propagation for LiDAR odometry, termed DSLO. It consists of a pyramid structure…
Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation
Yixiao Wang, Chen Tang, Lingfeng Sun +8
Diffusion models are promising for joint trajectory prediction and controllable generation in autonomous driving, but they face challenges of inefficient inference steps and high c…