In the summer of 2025, I had the privilege to experience competing in the ETH RobotX Summer School Challenge. This was an intensive, five-day team competition focused on the deployment of a modular, autonomous robot pipeline, covering all stages from perception to control. The competition took place as part of the ETH Robotics Summer School, an advanced program hosted by the ETH RobotX initiative and often co-located with the ARCHE (Advanced Robotic Capabilities for Hazardous Environments) event, specializing in search and rescue robotics.
The challenge required the rapid integration and tuning of existing algorithms and modules to construct a robust autonomous navigation stack on a rough-terrain Unmanned Ground Vehicle (UGV) for a simulated Search and Rescue (SAR) mission. The objective was the efficient autonomous exploration, localization, and artefact detection in a complex environment.
Results: Our team successfully won the ETH RobotX Summer School Challenge. Our integrated autonomous pipeline secured the victory by producing the most precise point cloud-based map and achieving the highest artefact detection rate among all competitors, confirming the stability and optimal tuning of our selected algorithms.
Impact: I served as the Team Lead, reinforcing my ability to manage time-critical robotics projects. This role focused on ensuring timely task completion (e.g., object recognition, state estimation) and seamless integration of all individually developed modules into the complete, high-reliability autonomous pipeline under firm time constraints.