8 papers
RAVEN: Reinforcement-Adaptive Visibility-Graph Planning for Robust Humanoid Navigation with Collision-Free MPC
Ruochen Hou, Shiqi Wang, Beom Jun Kim +3
Humanoid navigation in dynamic environments requires long-horizon planning while respecting short-horizon dynamic and safety constraints. Classical visibility-graph planners combin…
DexEXO: A Wearability-First Dexterous Exoskeleton for Operator-Agnostic Demonstration and Learning
Alvin Zhu, Mingzhang Zhu, Beom Jun Kim +10
Scaling dexterous robot learning is constrained by the difficulty of collecting high-quality demonstrations across diverse operators. Existing wearable interfaces often trade comfo…
WHED: A Wearable Hand Exoskeleton for Natural, High-Quality Demonstration Collection
Mingzhang Zhu, Alvin Zhu, Jose Victor S. H. Ramos +9
Scalable learning of dexterous manipulation remains bottlenecked by the difficulty of collecting natural, high-fidelity human demonstrations of multi-finger hands due to occlusion,…
A Hierarchical, Model-Based System for High-Performance Humanoid Soccer
Quanyou Wang, Mingzhang Zhu, Ruochen Hou +16
The development of athletic humanoid robots has gained significant attention as advances in actuation, sensing, and control enable increasingly dynamic, real-world capabilities. Ro…
A Generalization of CLAP from 3D Localization to Image Processing, A Connection With RANSAC & Hough Transforms
Ruochen Hou, Gabriel I. Fernandez, Alex Xu +1
In previous work, we introduced a 2D localization algorithm called CLAP, Clustering to Localize Across Possibilities, which was used during our championship win in RoboCup 2024…
CLAP: Clustering to Localize Across n Possibilities, A Simple, Robust Geometric Approach in the Presence of Symmetries
Gabriel I. Fernandez, Ruochen Hou, Alex Xu +2
In this paper, we present our localization method called CLAP, Clustering to Localize Across Possibilities, which helped us win the RoboCup 2024 adult-sized autonomous humanoid…