Commonsense reasoning for legged robot adaptation with vision-language models
AS Chen, AM Lessing, A Tang, G Chada… - arXiv preprint arXiv …, 2024 - arxiv.org
Legged robots are physically capable of navigating a diverse variety of environments and
overcoming a wide range of obstructions. For example, in a search and rescue mission, a …
overcoming a wide range of obstructions. For example, in a search and rescue mission, a …
Autonomous improvement of instruction following skills via foundation models
Intelligent instruction-following robots capable of improving from autonomously collected
experience have the potential to transform robot learning: instead of collecting costly …
experience have the potential to transform robot learning: instead of collecting costly …
Quadrupedgpt: Towards a versatile quadruped agent in open-ended worlds
While pets offer companionship, their limited intelligence restricts advanced reasoning and
autonomous interaction with humans. Considering this, we propose QuadrupedGPT, a …
autonomous interaction with humans. Considering this, we propose QuadrupedGPT, a …
One policy to run them all: an end-to-end learning approach to multi-embodiment locomotion
N Bohlinger, G Czechmanowski, M Krupka… - arXiv preprint arXiv …, 2024 - arxiv.org
Deep Reinforcement Learning techniques are achieving state-of-the-art results in robust
legged locomotion. While there exists a wide variety of legged platforms such as quadruped …
legged locomotion. While there exists a wide variety of legged platforms such as quadruped …
From Reward Shaping to Q-Shaping: Achieving Unbiased Learning with LLM-Guided Knowledge
X Wu - arXiv preprint arXiv:2410.01458, 2024 - arxiv.org
Q-shaping is an extension of Q-value initialization and serves as an alternative to reward
shaping for incorporating domain knowledge to accelerate agent training, thereby improving …
shaping for incorporating domain knowledge to accelerate agent training, thereby improving …
Enhancing Q-Learning with Large Language Model Heuristics
X Wu - arXiv preprint arXiv:2405.03341, 2024 - arxiv.org
Q-learning excels in learning from feedback within sequential decision-making tasks but
requires extensive sampling for significant improvements. Although reward shaping is a …
requires extensive sampling for significant improvements. Although reward shaping is a …
SARO: Space-Aware Robot System for Terrain Crossing via Vision-Language Model
The application of vision-language models (VLMs) has achieved impressive success in
various robotics tasks. However, there are few explorations for these foundation models …
various robotics tasks. However, there are few explorations for these foundation models …
Enhancing Robustness in Language-Driven Robotics: A Modular Approach to Failure Reduction
É Garrabé, P Teixeira, M Khoramshahi… - arXiv preprint arXiv …, 2024 - arxiv.org
Recent advances in large language models (LLMs) have led to significant progress in
robotics, enabling embodied agents to better understand and execute open-ended tasks …
robotics, enabling embodied agents to better understand and execute open-ended tasks …
Interactive Navigation of Quadruped Robots in Challenging Environments using Large Language Models
Robotic navigation in complex environments remains a critical research challenge. Notably,
quadrupedal navigation has made significant progress due to the terrain adaptivity and …
quadrupedal navigation has made significant progress due to the terrain adaptivity and …