6 papers
SigLoMa: Learning Open-World Quadrupedal Loco-Manipulation from Ego-Centric Vision
Shiyi Chen, Haiyi Liu, Mingye Yang +2
Designing an open-world quadrupedal loco-manipulation system is highly challenging. Traditional reinforcement learning frameworks utilizing exteroception often suffer from extreme…
Zero-Shot UAV Navigation in Forests via Relightable 3D Gaussian Splatting
Zinan Lv, Yeqian Qian, Chen Sang +3
UAV navigation in unstructured outdoor environments using passive monocular vision is hindered by the substantial visual domain gap between simulation and reality. While 3D Gaussia…
General Humanoid Whole-Body Control via Pretraining and Fast Adaptation
Zepeng Wang, Jiangxing Wang, Shiqing Yao +8
Learning a general whole-body controller for humanoid robots remains challenging due to the diversity of motion distributions, the difficulty of fast adaptation, and the need for r…
From Experts to a Generalist: Toward General Whole-Body Control for Humanoid Robots
Yuxuan Wang, Ming Yang, Ziluo Ding +5
Achieving general agile whole-body control on humanoid robots remains a major challenge due to diverse motion demands and data conflicts. While existing frameworks excel in trainin…
JAEGER: Dual-Level Humanoid Whole-Body Controller
Ziluo Ding, Haobin Jiang, Yuxuan Wang +7
This paper presents JAEGER, a dual-level whole-body controller for humanoid robots that addresses the challenges of training a more robust and versatile policy. Unlike traditional…
Robotic Sim-to-Real Transfer for Long-Horizon Pick-and-Place Tasks in the Robotic Sim2Real Competition
Ming Yang, Hongyu Cao, Lixuan Zhao +2
This paper presents a fully autonomous robotic system that performs sim-to-real transfer in complex long-horizon tasks involving navigation, recognition, grasping, and stacking in…