5 citations · 6 across the 5 of their papers we have counts for
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…
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…
From Screen to Stage: Kid Cosmo, A Life-Like, Torque-Controlled Humanoid for Entertainment Robotics
Havel Liu, Mingzhang Zhu, Arturo Moises Flores Alvarez +8
Humanoid robots represent the cutting edge of robotics research, yet their potential in entertainment remains largely unexplored. Entertainment as a field prioritizes visuals and f…
Feasibility Study of LIMMS, A Multi-Agent Modular Robotic Delivery System with Various Locomotion and Manipulation Modes
Taoyuanmin Zhu, Gabriel I. Fernandez, Colin Togashi +2
The logistics of transporting a package from a storage facility to the consumer's front door usually employs highly specialized robots often times splitting sub-tasks up to differe…
Deep Reinforcement Learning with Linear Quadratic Regulator Regions
Gabriel I. Fernandez, Colin Togashi, Dennis W. Hong +1
Practitioners often rely on compute-intensive domain randomization to ensure reinforcement learning policies trained in simulation can robustly transfer to the real world. Due to u…