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Guanqi He

9 accepted papers

2025

ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills

RSS 2025poster

Humanoid robots hold the potential for unparalleled versatility by performing human-like, whole-body skills. However, achieving agile and coordinated whole-body motions remains a significant challenge due to the dynamics mismatch between simulation and real-world physics. Existing approaches, such a…

Cited by 15PDFcodeScholar
2025

Flying Hand: End-Effector-Centric Framework for Versatile Aerial Manipulation Teleoperation and Policy Learning

RSS 2025poster

Aerial manipulation has recently attracted increasing interest from both industry and academia. Previous approaches have demonstrated success in various specific tasks. However, their hardware design and control frameworks are often tightly coupled with particular tasks, limiting the development of…

Cited by 1PDFScholar
2025

Hold My Beer: Learning Gentle Humanoid Locomotion and End-Effector Stabilization Control

CoRL 2025poster

Can your humanoid walk up and hand you a full cup of beer—without spilling a drop? While humanoids are increasingly featured in flashy demos—dancing, delivering packages, traversing rough terrain—fine-grained control during locomotion remains a significant challenge. In particular, stabilizing a fil…

Cited by 0SourceScholar
2025

Sampling-based System Identification with Active Exploration for Legged Sim2Real Learning

CoRL 2025oral

Sim-to-real discrepancies hinder learning-based policies from achieving high-precision tasks in the real world. While Domain Randomization (DR) is commonly used to bridge this gap, it often relies on heuristics and can lead to overly conservative policies with degrading performance when not properly…

Cited by 0SourcecodeScholar
2025

Self-Supervised Meta-Learning for All-Layer DNN-Based Adaptive Control with Stability Guarantees

ICRA 2025

A critical goal of adaptive control is enabling robots to rapidly adapt in dynamic environments. Recent studies have developed a meta-learning-based adaptive control scheme, which uses meta-learning to extract nonlinear features (represented by Deep Neural Networks (DNNs)) from offline data, and use

Cited by 6SourceScholar
2024

Aerial Interaction with Tactile Sensing

ICRA 2024poster

While the field of autonomous Uncrewed Aerial Vehicles (UAVs) has grown rapidly, most applications only focus on passive visual tasks. Aerial interaction aims to execute tasks involving physical interactions, which offers a way to assist humans in high-altitude and high-risk operations. Tactile sens…

Cited by 15SourceScholar
2024

Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion

RSS 2024poster

Legged robots navigating cluttered environments must be jointly agile for efficient task execution and safe to avoid collisions with obstacles or humans. Existing studies either develop conservative controllers (< 1.0 m/s) to ensure safety, or focus on agility without considering potentially fatal c…

2024

Flying Calligrapher: Contact-Aware Motion and Force Planning and Control for Aerial Manipulation

RA-L 2024

Aerial manipulation has gained interest in completing high-altitude tasks that are challenging for human workers, such as contact inspection and defect detection, etc. Previous research has focused on maintaining static contact points or forces. This letter addresses a more general and dynamic task:

Cited by 22SourceScholar
2023

Image-Based Visual Servo Control for Aerial Manipulation Using a Fully-Actuated UAV

IROS 2023poster

Using Unmanned Aerial Vehicles (UAVs) to per-form high-altitude manipulation tasks beyond just passive visual application can reduce the time, cost, and risk of human workers. Prior research on aerial manipulation has relied on either ground truth state estimate or GPS/total station with some Simult…

Cited by 15SourceScholar