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Ruiqi Yu

6 accepted papers

2026

START: Traversing Sparse Footholds With Terrain Reconstruction

RA-L 2026

Traversing terrains with sparse footholds like legged animals presents a promising yet challenging task for quadruped robots, as it requires precise environmental perception and agile control to secure safe foot placement while maintaining dynamic stability. Model-based hierarchical controllers exce

Cited by 3SourceScholar
2026

START: Traversing Sparse Footholds with Terrain Reconstruction

ICRA 2026poster

Traversing terrains with sparse footholds like legged animals presents a promising yet challenging task for quadruped robots, as it requires precise environmental perception and agile control to secure safe foot placement while maintaining dynamic stability. Model-based hierarchical controllers exce…

2026

SketchAssist: A Practical Assistant for Semantic Edits and Precise Local Redrawing

CVPR 2026

Sketch editing requires jointly handling high-level semantic changes and precise local redrawing, a combination that is particularly challenging for sparse, style-sensitive line art. Unlike natural images, sketches rely on minimal visual cues, making it difficult for existing methods to reconcile gl

Cited by 0SourceScholar
2025

SerialGen: Personalized Image Generation by First Standardization Then Personalization

CVPR 2025poster

In this work, we are interested in achieving both high text controllability and whole-body appearance consistency in the generation of personalized human characters. We propose a novel framework, named SerialGen, which is a serial generation method consisting of two stages: first, a standardization…

Cited by 1SourcePDFScholar
2024

PIE: Parkour With Implicit-Explicit Learning Framework for Legged Robots

RA-L 2024

Parkour presents a highly challenging task for legged robots, requiring them to traverse various terrains with agile and smooth locomotion. This necessitates comprehensive understanding of both the robot's own state and the surrounding terrain, despite the inherent unreliability of robot perception

Cited by 49SourceScholar
2024

Toward Understanding Key Estimation in Learning Robust Humanoid Locomotion

IROS 2024poster

Accurate state estimation plays a critical role in ensuring the robust control of humanoid robots, particularly in the context of learning-based control policies for legged robots. However, there is a notable gap in analytical research concerning estimations. Therefore, we endeavor to further unders…

Cited by 6SourceScholar