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20242026
most citedDexterous Manipulation through Imitation Learning: A Survey

2 citations · 3 across the 12 of their papers we have counts for

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10 papers · 1 filter

cs.RO2026

UniReLo: Learning a Unified Humanoid Policy from Fall Recovery to Locomotion across Diverse Terrains

Xiaoyu Xu, Zhiming Chen, Yuenan Zhao +2

Reliable fall recovery, which commonly aims at attaining a nominal upright posture, is essential for the autonomous operation of humanoid robots in unstructured field environments.…

cs.RO2025

SafeFall: Learning Protective Control for Humanoid Robots

Ziyu Meng, Tengyu Liu, Le Ma +4

Bipedal locomotion makes humanoid robots inherently prone to falls, causing catastrophic damage to the expensive sensors, actuators, and structural components of full-scale robots.…

cs.RO2025

Vision-Language Model Predictive Control for Manipulation Planning and Trajectory Generation

Jiaming Chen, Wentao Zhao, Ziyu Meng +4

Model Predictive Control (MPC) is a widely adopted control paradigm that leverages predictive models to estimate future system states and optimize control inputs accordingly. Howev…

cs.RO2025★ 2 cited

Dexterous Manipulation through Imitation Learning: A Survey

Shan An, Ziyu Meng, Chao Tang +9

Dexterous manipulation, which refers to the ability of a robotic hand or multi-fingered end-effector to skillfully control, reorient, and manipulate objects through precise, coordi…

cs.RO2025

StyleLoco: Generative Adversarial Distillation for Natural Humanoid Robot Locomotion

Le Ma, Ziyu Meng, Tengyu Liu +4

Humanoid robots are anticipated to acquire a wide range of locomotion capabilities while ensuring natural movement across varying speeds and terrains. Existing methods encounter a…

cs.RO2024

Learning Instruction-Guided Manipulation Affordance via Large Models for Embodied Robotic Tasks

Dayou Li, Chenkun Zhao, Shuo Yang +3

We study the task of language instruction-guided robotic manipulation, in which an embodied robot is supposed to manipulate the target objects based on the language instructions. I…

cs.RO2024

Where to Fetch: Extracting Visual Scene Representation from Large Pre-Trained Models for Robotic Goal Navigation

Yu Li, Dayou Li, Chenkun Zhao +3

To complete a complex task where a robot navigates to a goal object and fetches it, the robot needs to have a good understanding of the instructions and the surrounding environment…

cs.RO2024

MPGNet: Learning Move-Push-Grasping Synergy for Target-Oriented Grasping in Occluded Scenes

Dayou Li, Chenkun Zhao, Shuo Yang +3

This paper focuses on target-oriented grasping in occluded scenes, where the target object is specified by a binary mask and the goal is to grasp the target object with as few robo…

cs.RO2024

Integrating Controllable Motion Skills from Demonstrations

Honghao Liao, Zhiheng Li, Ziyu Meng +3

The expanding applications of legged robots require their mastery of versatile motion skills. Correspondingly, researchers must address the challenge of integrating multiple divers…

cs.RO2024★ 1 cited

VLMPC: Vision-Language Model Predictive Control for Robotic Manipulation

Wentao Zhao, Jiaming Chen, Ziyu Meng +3

Although Model Predictive Control (MPC) can effectively predict the future states of a system and thus is widely used in robotic manipulation tasks, it does not have the capability…