2 citations · 3 across the 6 of their papers we have counts for
6 papers
SPOT: Spatial Perception-Oriented Long-Horizon Humanoid Teleoperation
Lixing Fang, Ziyan Xiong, Sunli Chen +2
High-quality demonstration data is becoming a central bottleneck for training general-purpose humanoid robots. While recent humanoid teleoperation systems have made substantial pro…
DLO-Lab: Benchmarking Deformable Linear Object Manipulations with Differentiable Physics
Junyi Cao, Yian Wang, Ziyan Xiong +3
We address the challenge of enabling robots to manipulate deformable linear objects (DLOs), such as ropes, cables, and rubber bands. Prior work has primarily focused on narrow, tas…
ExtremControl: Low-Latency Humanoid Teleoperation with Scaled Velocity Feedforward
Ziyan Xiong, Lixing Fang, Junyun Huang +3
Building a low-latency humanoid teleoperation system is essential for collecting diverse reactive and dynamic demonstrations. However, end-to-end latencies in existing approaches c…
MQE: Unleashing the Power of Interaction with Multi-agent Quadruped Environment
Ziyan Xiong, Bo Chen, Shiyu Huang +3
The advent of deep reinforcement learning (DRL) has significantly advanced the field of robotics, particularly in the control and coordination of quadruped robots. However, the com…
Finetuning Offline World Models in the Real World
Yunhai Feng, Nicklas Hansen, Ziyan Xiong +2
Reinforcement Learning (RL) is notoriously data-inefficient, which makes training on a real robot difficult. While model-based RL algorithms (world models) improve data-efficiency…
Neural Collision Detection for Deformable Objects
Ryan S. Zesch, Bethany R. Witemeyer, Ziyan Xiong +2
We propose a neural network-based approach for collision detection with deformable objects. Unlike previous approaches based on bounding volume hierarchies, our neural approach doe…