Yunfan Gao

PhD Candidate

Advanced Autonomous Systems Department

Robert Bosch GmbH, Corporate Research

Yunfan Gao obtained the bachelor degree in Electronic engineering from Fudan University, Shanghai, China in 2019. Then she took her master study in Robotics, Systems and Control at ETH Zurich, and graduated in January 2022. Her master thesis was about the integration of projection mapping with mobile robots. Recently in March 2022, she started carrying out a PhD at Bosch Research with the topic “Safety and Robustness in Mobile Robot Motion Planning”.

Project description

This PhD project is about motion planning for industrial robots and service robots. The aim is to run mobile robots efficiently with safety guaranteed. Currently, the common approach in industry to achieve safety is to deploy a separate safety controller. The controller alters the control commands made by the motion planner if necessary. This approach is too conservative as large portions of the space are marked as unsafe. To achieve safety in motion planning non-conservatively is challenging. Possible research directions include tighter integration between the motion planning and the safety control, prediction of surrounding agents’ trajectories, as well as real-time execution.


Frey, Jonathan; Gao, Yunfan; Messerer, Florian; Lahr, Amon; Zeilinger, Melanie N.; Diehl, Moritz

Efficient Zero-Order Robust Optimization for Real-Time Model Predictive Control with Acados Working paper


Abstract | Links | BibTeX


Gao, Yunfan; Messerer, Florian; Frey, Jonathan; Duijkeren, Niels; Diehl, Moritz

Collision-free Motion Planning for Mobile Robots by Zero-order Robust Optimization-based MPC Proceedings Article

In: 2023 European Control Conference (ECC), pp. 1-6, IEEE, Bucharest, Romania, 2023, ISBN: 978-3-907144-08-4.

Abstract | Links | BibTeX