Vision System and Depth Processing for DRC-HUBO+

TL;DR

This paper introduces a robust vision and depth processing system for DRC-HUBO+ that accurately captures 3D scene information and improves depth map quality, enabling reliable object detection and pose estimation in challenging environments.

Contribution

It presents a novel depth-map upsampling method that effectively handles outliers and enhances depth accuracy for robotic applications.

Findings

Outperforms existing algorithms on synthetic datasets

Demonstrates robustness in real-world challenging conditions

Enables precise object detection and pose estimation

Abstract

This paper presents a vision system and a depth processing algorithm for DRC-HUBO+, the winner of the DRC finals 2015. Our system is designed to reliably capture 3D information of a scene and objects robust to challenging environment conditions. We also propose a depth-map upsampling method that produces an outliers-free depth map by explicitly handling depth outliers. Our system is suitable for an interactive robot with real-world that requires accurate object detection and pose estimation. We evaluate our depth processing algorithm over state-of-the-art algorithms on several synthetic and real-world datasets.