2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.RO2026
SIMPLE: Simulation-Based Policy Learning and Evaluation for Humanoid Loco-manipulation
Songlin Wei, Zhenhao Ni, Jie Liu +9
Humanoid foundation models are advancing faster than we can evaluate them. While real-world testing is expensive and difficult to reproduce, existing simulation benchmarks focus pr…
cs.RO2026
: An Open Foundation Model Towards Universal Humanoid Loco-Manipulation
Songlin Wei, Hongyi Jing, Boqian Li +12
We introduce (Psi-Zero), an open foundation model to address challenging humanoid loco-manipulation tasks. While existing approaches often attempt to address this fundamental…
cs.RO2023★ 2 cited
GRID: Scene-Graph-based Instruction-driven Robotic Task Planning
Zhe Ni, Xiaoxin Deng, Cong Tai +5
Recent works have shown that Large Language Models (LLMs) can facilitate the grounding of instructions for robotic task planning. Despite this progress, most existing works have pr…