8 papers
GuideWalk: Learning Unified Autonomous Navigation and Locomotion for Humanoid Robots across Versatile Terrains
Haoxuan Han, Chen Chen, Linao Gong +6
Humanoid robots have achieved strong locomotion capabilities, but reliable navigation on versatile terrains remains challenging because obstacle avoidance must be coordinated with…
T-GMP: Terrain-conditioned Generative Motion Priors for Versatile and Natural Humanoid Locomotion
Junhong Guo, Hao Hu, Chen Chen +6
Achieving both anthropomorphic naturalness and robust terrain traversal remains a fundamental challenge in humanoid locomotion. Existing Reinforcement Learning (RL) approaches typi…
Equivariant Filter Transformations for Consistent and Efficient Visual--Inertial Navigation
Chungeng Tian, Fenghua He, Ning Hao
This paper presents an equivariant filter (EqF) transformation approach for visual--inertial navigation. By establishing analytical links between EqFs with different symmetries, th…
CLIDD: Cross-Layer Independent Deformable Description for Efficient and Discriminative Local Feature Representation
Haodi Yao, Fenghua He, Ning Hao +1
Robust local feature representations are essential for spatial intelligence tasks such as robot navigation and augmented reality. Establishing reliable correspondences requires des…
Unobservable Subspace Evolution and Alignment for Consistent Visual-Inertial Navigation
Chungeng Tian, Fenghua He, Ning Hao
The inconsistency issue in the Visual-Inertial Navigation System (VINS) is a long-standing and fundamental challenge. While existing studies primarily attribute the inconsistency t…
T-ESKF: Transformed Error-State Kalman Filter for Consistent Visual-Inertial Navigation
Chungeng Tian, Ning Hao, Fenghua He
This paper presents a novel approach to address the inconsistency problem caused by observability mismatch in visual-inertial navigation systems (VINS). The key idea involves apply…