Hardware & whole-body control
Designing aerial manipulation hardware and whole-body controllers, including model predictive control (MPC), to coordinate flight and manipulation during physical interaction.
Robotics & Embodied Intelligence
Yufei Jiang
Ph.D. Candidate in Aerospace Engineering
Penn State University
Enabling aerial robots to perceive, plan, and interact with the world.
My research focuses on aerial manipulation: moving flying robots beyond observation toward physical interaction. I work at the intersection of perception, planning, control, and learning to build reliable autonomous systems.
Research interests
From hardware to embodied intelligencePerception & planning
Exploring visual and LiDAR perception, diverse environment representations, and model-based and learning-based planning for aerial manipulation in complex environments.
Embodied intelligence
Exploring how large language models (LLMs) and vision-language-action (VLA) models connect high-level reasoning, task planning, and physical action for intelligent aerial manipulation.
Latest news
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Our paper, AM-Bench: A Modular Simulation Suite and Benchmark for Aerial Manipulation Policy Learning, was accepted to the Conference on Robot Learning (CoRL 2026)!
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Our short paper, Aerial Manipulation in the Wild with Onboard Perception, Policy Learning, and Whole-Body Control, was accepted for a spotlight presentation and poster at the 5th Workshop on Mobile Manipulation and Embodied Intelligence (MoMA.v5) at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026) in Pittsburgh!
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I passed my Ph.D. Comprehensive Exam!
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I passed my Ph.D. English Proficiency Exam!
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I earned my Master of Science degree en route to my Ph.D.!
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I received the Harry G. Miller Fellowships in Engineering!
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I passed my Ph.D. Qualifying Exam!
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I presented my latest research at the Aerospace Seminar Series at Penn State.
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Our papers, A Self-Supervised Learning Approach with Differentiable Optimization for UAV Trajectory Planning and Aerial Manipulation with Contact-Aware Onboard Perception and Hybrid Control, were accepted to the IEEE International Conference on Robotics and Automation (ICRA 2026)
Selected publications
All publications
2026 ICRA
A Self-Supervised Learning Approach with Differentiable Optimization for UAV Trajectory Planning
* Equal contribution
IEEE International Conference on Robotics and Automation (ICRA) · 2026
A self-supervised UAV planning framework that combines learned perception with differentiable trajectory optimization and adaptive time allocation.
2026 ICRA
Aerial Manipulation with Contact-Aware Onboard Perception and Hybrid Control
* Equal contribution
IEEE International Conference on Robotics and Automation (ICRA) · 2026
A fully onboard perception–control pipeline for accurate motion estimation and stable, force-regulated aerial interaction without external motion capture.
2026 CoRL
AM-Bench: A Modular Simulation Suite and Benchmark for Aerial Manipulation Policy Learning
Conference on Robot Learning (CoRL) · 2026
A modular simulation suite and benchmark for studying how aerial-robot embodiment, low-level control, disturbances, and policy design jointly affect manipulation performance.
Beyond the lab
A little more about me
Outside research, I enjoy playing badminton, basketball, and tennis. I also love cooking, trying new recipes, and sharing good food with friends. I’m always happy to join a game or swap recipe ideas!
Get in touch
Let’s connect.
I’m happy to chat about research, collaboration, and professional opportunities. Reach out by email or connect with me on LinkedIn.