Project Template - Fabio Hübel

Overview

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.

Key Features

Rapid System Integration & Deployment Successfully integrated and configured existing software components (including state estimation, SLAM, and motion planning algorithms) into a cohesive and operational system within the demanding five-day timeframe.
Real-time Sensor Fusion Tuning Achieved reliable state estimation under challenging conditions by tuning existing sensor fusion algorithms (EKF) to optimally combine pre-calibrated LiDAR, wheel encoder and inertial data for robust navigation.
Path Planning & Control Optimization Optimized an existing path-planning and low-level control scheme for the target UGV, enabling it to execute autonomous navigation, obstacle avoidance, and precise positioning necessary to meet the SAR mission objectives.

Team & Supervision

Fabio Hübel

Team Leader

ETH Zürich

Ali Karakullukcu

Team Member

TU Munich

Alpay Ozkan

Team Member

ETH Zürich

Perla Rocha

Team Member

FAU Erlangen

Alessio Rimoldi

Team Member

ETH Zürich

Emma Seabrook

Team Member

ISAE-SUPAERO

Dr. Cesar Cadena

Event organiser

Robotic Systems Lab, ETH Zürich

Project Gallery

My RobotX Summer School Team. From left to right: Ali, Alpay, Perla, Alessio, Emma and me.

Point cloud representation of the environment captured during the RobotX challenge.

Our winning moment at the ETH RobotX Summer School Challenge 2025.

The rover robot in action, exploring the environment during the ETH RobotX Summer School Challenge.

Results & Impact

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.

ETH RobotX Summer School

Overview

Key Features

Technologies & Tools

Team & Supervision

Fabio Hübel

Ali Karakullukcu

Alpay Ozkan

Perla Rocha

Alessio Rimoldi

Emma Seabrook

Dr. Cesar Cadena

Project Gallery

Results & Impact

References