5 papers
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…
Model Predictive Control with Visibility Graphs for Humanoid Path Planning and Tracking Against Adversarial Opponents
Ruochen Hou, Gabriel I. Fernandez, Mingzhang Zhu +1
In this paper we detail the methods used for obstacle avoidance, path planning, and trajectory tracking that helped us win the adult-sized, autonomous humanoid soccer league in Rob…
Fast and Robust Localization for Humanoid Soccer Robot via Iterative Landmark Matching
Ruochen Hou, Mingzhang Zhu, Hyunwoo Nam +2
Accurate robot localization is essential for effective operation. Monte Carlo Localization (MCL) is commonly used with known maps but is computationally expensive due to landmark m…