Sihao Sun

Sihao Sun

Researcher in Robotics

Delft University of Technology

Biography

I am a researcher with a focus on planning, estimation, and control of aerial robotic systems. My work has been recognized with the prestigious Best Paper Award of IEEE Robotics and Automation Letters. My research on aerial robot fault-tolerant control and perception has been featured in well-regarded media outlets like IEEE Spectrum. I’m the winner of the Veni grant as part of the Dutch Research Council (NWO) talent program.

I’m currently a researcher at the deparment of Cognitive Robotics (CoR) of Delft University of Technology. From 2022 to 2023, I have been a postdoctoral researcher at the Robotics and Mechatronics (RaM) group at the University of Twente, collaborating with Prof. Antonio Franchi. Prior to this, from 2020 to 2021, I worked as a postdoctoral researcher at the Robotics and Perception Group (RPG) at the University of Zurich under the guidance of Prof. Davide Scaramuzza.

In December 2020, I earned my PhD in Aerospace Engineering from the Control and Simulation Group (C&S) at Delft University of Technology, supervised by Dr. Coen de Visser and Prof. Guido de Croon. My doctoral thesis has addressed the fault-tolerant control problem of aerial robots subject to significant dynamical uncertainties.

Interests

  • Aerial Robotics
  • Robotics Perception
  • Incremental Nonlinear Control
  • Multi-robot Systems

Education

  • PhD in Aerospace Engineering, 2020

    Delft University of Technology

News

  • Sep 26, 2025. We have a paper published on Nature🎉🎉🎉. This work is led by collaborators from WINDY Lab, Westlake University, addressing the challenge of downwash interference when two aerial manipulators are in vertical-stack proximal flights.

  • Aug 30, 2025. Congratulations to my MSc student, Shantnav Agarwal, for successfully defending his thesis about Cooperative Aerial Manipulation with Imitation Learning with 🎉Cum-Laude distinction🎉!

  • Aug 1, 2025. Our paper on Multi-agent RL for Aerial Manipulation has been accepted by CoRL! Check it out

  • July 21, 2025. Congratulations to my MSc student Jack Zeng for successfully defending his thesis about Cable-suspended Aerial Manipulation with Multi-Agent RL with Cum-Laude ditinction! 🎉🎉

  • Feb 15, 2024. I have been appointed as an Associate Editor of the 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024).

  • January 15, 2024. I have joined the department of Cognitive Robotics as a researcher funded by the Veni Grant. A new journey now begins!🦾🤖🦿

  • October 17, 2023. I have been appointed an Associate Editor of the IEEE Robotics and Automation Letters (RA-L).

  • August 3, 2023. I have won the prestigious Veni grant from Dutch Research Council.🏆

Research Projects

Accurate Aerial Manipulation under Uncertainties

This project performs mechatronics design and developes novel algorithms to increase the accuracy of aerial robotic manipulators under dynamical uncertainties.

Agile Flight Control for Drones

This project aims at designing flight controllers to achieve agile flight for drones, with the aim of improving its performance in time-critical missions.

Quadrotor Fault Tolerant Flight Control

This project leads to a set of fault-tolerant control algorithms for a quadrotor with motor failures in realistic scenarios, such as withstanding strong winds up to 10m/s, and recovery from extreme conditions.

Aerodynamic Modeling Identification for Multi-Rotor Drones

This project aims at obtaining a set of aerodynamic model for drones using system identification and machine learning technique.

High Efficiency Air Cargo Design

A student project with the aim of desining an unmanned air-cargo with high aerodynamic and structral efficiency.

Publication list

Uncertainty Modeling Enabled Meta Adaptive Control for Aerial Manipulators

Meta Adaptive Control for Aerial Manipulators.
Shiqi Gao, Haichao Hong, Sihao Sun, Lingkun Luo, Shiqiang Hu
PDF Project DOI
Uncertainty Modeling Enabled Meta Adaptive Control for Aerial Manipulators

Nonlinear MPC for Quadrotor Fault-Tolerant Control

We study the performance of using nonlinear MPC on quadrotor fail-safe problem. The result is amazing.
Nan Fang, Sihao Sun, Philipp Foehn, Davide Scaramuzza
PDF Project Video
Nonlinear MPC for Quadrotor Fault-Tolerant Control

A Comparative Study of Nonlinear MPC and Differential-Flatness-Based Control for Quadrotor Agile Flight

We systematically compare two state-of-the-art flight controllers for quadcopter agile flights, nonlinear MPC and differential-flatness-based controller.
Sihao Sun, Angel Romero, Philipp Foehn, Elia Kaufmann, Davide Scaramuzza
PDF Project Video
A Comparative Study of Nonlinear MPC and Differential-Flatness-Based Control for Quadrotor Agile Flight

Model Predictive Contouring Control for Near-Time-Optimal Quadrotor Flight

This work proposes a novel control methods for quadcopter agile flights using model-predictive-contouring control.
Angel Romero, Sihao Sun, Philipp Foehn, Davide Scaramuzza
PDF Project Video
Model Predictive Contouring Control for Near-Time-Optimal Quadrotor Flight

Performance, Precision, and Payloads: Adaptive Nonlinear MPC for Quadrotors

We propose L1-MPC, an adaptive-model-predictive control framework showing impressive performance against model uncertainties and disturbances.
Drew Hanover, Philipp Foehn, Sihao Sun, Elia Kaufmann, Davide Scaramuzza
PDF Project Video
Performance, Precision, and Payloads: Adaptive Nonlinear MPC for Quadrotors

Autonomous Quadrotor Flight despite Rotor Failure with Onboard Vision Sensors Frames vs. Events

This algorithm uses only onboard vision sensors to control a quadrotor after complete faliure of a rotor, without the aid of GPS, UWB, or other external sensors.
Sihao Sun, Giovanni Cioffi, Coen de Visser, Davide Scaramuzza
PDF Code Project Video IEEE Spectrum
Autonomous Quadrotor Flight despite Rotor Failure with Onboard Vision Sensors Frames vs. Events

Incremental Nonlinear Fault-Tolerant Control of a Quadrotor With Complete Loss of Two Opposing Rotors

This work, for the first time, applies Incremental Nonlinear Dynamic Inversion controller on an under-actuated control system, namely a quadrotor with complete loss of two opposing rotors. A high-speed wind-tunnel flight test demonstrates the robustness of this method.
Sihao Sun, Xuerui Wang, Qiping Chu, Coen de Visser
PDF Code Project Video
Incremental Nonlinear Fault-Tolerant Control of a Quadrotor With Complete Loss of Two Opposing Rotors

High-speed flight of quadrotor despite loss of single rotor

We propose a flight controller to achieve high-speed flights of a quadrotor with one rotor entirely off. Flight tests in the wind tunnel show robustness of our controller in the presence of significant aerodynamic effects.
Sihao Sun, Leon Sijbers, Xuerui Wang, Coen de Visser
PDF Project Video IEEE Spectrum
High-speed flight of quadrotor despite loss of single rotor

Upset Recovery Control for Quadrotors Subjected to a Complete Rotor Failure from Large Initial Disturbances

We introduce a flight controller that can recover a quadrotor with one rotor complete off from arbitrary initial orientations and body rates.
Sihao Sun, Matthias Beart, Bram Strack van Schijndel, Coen de Visser
PDF Project Video ICRA online presentation Master Thesis
Upset Recovery Control for Quadrotors Subjected to a Complete Rotor Failure from Large Initial Disturbances

Quadrotor gray-box model identification from high-speed flight data

In this work, we presented a gray-box aerodynamic model for a quadrotor identified from windtunnel high-speed flight data, using a step-wise regression algorithm.
Sihao Sun, Coen de Visser, Qiping Chu
PDF Code Project Conference Version
Quadrotor gray-box model identification from high-speed flight data

Quadrotor safe flight envelope prediction in the high-speed regime: A Monte-Carlo approach

A sampling based approach for estimating the reachable set of a quadrotor in high-speed regime to predict its (dynamic) flight envelope.
Sihao Sun, Coen de Visser
PDF Slides
Quadrotor safe flight envelope prediction in the high-speed regime: A Monte-Carlo approach

Quadrotor fault tolerant incremental sliding mode control driven by sliding mode disturbance observers

This work introduces a novel control method named Incremental Sliding Mode Control, which greatly reduces model dependency and improves the robustness against uncertainties. The algorithm has been validated in a quadrotor fault-tolerant control problem in real flight.
Xuerui Wang, Sihao Sun, Erik-Jan van Kampen, Qiping Chu
PDF Project
Quadrotor fault tolerant incremental sliding mode control driven by sliding mode disturbance observers