Reshaping Robot Trajectories Using Natural Language Commands: A Study of Multi-Modal Data Alignment Using Transformers-Reference-Cited by-同舟云学术

Reshaping Robot Trajectories Using Natural Language Commands: A Study of Multi-Modal Data Alignment Using Transformers

Published:2022-10-23 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
language:
Short-container-title:

Author:

Bucker Arthur¹,Figueredo Luis¹,Haddadinl Sami¹,Kapoor Ashish²,Ma Shuang²,Bonatti Rogerio²

Affiliation:

1. Technische Universität München

2. Microsoft

Publisher

IEEE

Link

Reference46 articles.

1. Semantically grounded object matching for robust robotic scene rearrangement;goodwin;ArXiv Preprint,2021

2. Vision-and-dialog navigation;thomason;Conference on Robot Learning,0

5. From language to goals: Inverse reinforcement learning for vision-based instruction following;fu;ArXiv Preprint,2019

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

3. EAI-SIM: An Open-Source Embodied AI Simulation Framework with Large Language Models;2024 IEEE 18th International Conference on Control & Automation (ICCA);2024-06-18

4. DAIM-HRI: A new Human-Robot Integration Technology for Industries;2024 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO);2024-05-20