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20222024
most citedPoint-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training

118 citations · 143 across the 21 of their papers we have counts for

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8 papers · 1 filter

cs.RO2024★ 1 cited

Exploring Spatial Representation to Enhance LLM Reasoning in Aerial Vision-Language Navigation

Yunpeng Gao, Zhigang Wang, Pengfei Han +3

Aerial Vision-and-Language Navigation (VLN) is a novel task enabling Unmanned Aerial Vehicles (UAVs) to navigate in outdoor environments through natural language instructions and v…

cs.RO2024

COHERENT: Collaboration of Heterogeneous Multi-Robot System with Large Language Models

Kehui Liu, Zixin Tang, Dong Wang +3

Leveraging the powerful reasoning capabilities of large language models (LLMs), recent LLM-based robot task planning methods yield promising results. However, they mainly focus on…

cs.RO2024

AlignBot: Aligning VLM-powered Customized Task Planning with User Reminders Through Fine-Tuning for Household Robots

Zhaxizhuoma Zhaxizhuoma, Pengan Chen, Ziniu Wu +7

This paper presents AlignBot, a novel framework designed to optimize VLM-powered customized task planning for household robots by effectively aligning with user reminders. In domes…

cs.RO2024

Depth Helps: Improving Pre-trained RGB-based Policy with Depth Information Injection

Xincheng Pang, Wenke Xia, Zhigang Wang +4

3D perception ability is crucial for generalizable robotic manipulation. While recent foundation models have made significant strides in perception and decision-making with RGB-bas…

cs.RO2024

KOI: Accelerating Online Imitation Learning via Hybrid Key-state Guidance

Jingxian Lu, Wenke Xia, Dong Wang +4

Online Imitation Learning struggles with the gap between extensive online exploration space and limited expert trajectories, hindering efficient exploration due to inaccurate rewar…

cs.RO2024

Learning Manipulation by Predicting Interaction

Jia Zeng, Qingwen Bu, Bangjun Wang +12

Representation learning approaches for robotic manipulation have boomed in recent years. Due to the scarcity of in-domain robot data, prevailing methodologies tend to leverage larg…

cs.RO2023

Kinematic-aware Prompting for Generalizable Articulated Object Manipulation with LLMs

Wenke Xia, Dong Wang, Xincheng Pang +4

Generalizable articulated object manipulation is essential for home-assistant robots. Recent efforts focus on imitation learning from demonstrations or reinforcement learning in si…

cs.RO2023

Robust Quadrupedal Locomotion via Risk-Averse Policy Learning

Jiyuan Shi, Chenjia Bai, Haoran He +6

The robustness of legged locomotion is crucial for quadrupedal robots in challenging terrains. Recently, Reinforcement Learning (RL) has shown promising results in legged locomotio…