RoboCup Rescue 2025 Team Description Paper UruBots

TL;DR

The paper addresses the RoboCup Rescue League task of autonomous exploration, victim detection, and manipulation in unknown environments. The authors present an integrated system built around the LIMO platform with a depth camera, 2D LiDAR, and a 4-DOF PincherX-100 manipulator, all orchestrated by a ROS-based mission planner. Core contributions include adopting Google Cartographer ROS for SLAM, a YOLOv5-based detector for people and PPE, and a ROS-enabled manipulation workflow, demonstrated through qualification-style experiments on autonomous navigation in a mapped scenario. The work aims to enable Team UruBots' first RoboCup Rescue entry and to contribute their hardware-software stack as open-source assets for the Rescue community, promoting learning and collaboration across teams.

Abstract

This paper describes the approach used by Team UruBots for participation in the 2025 RoboCup Rescue Robot League competition. Our team aims to participate for the first time in this competition at RoboCup, using experience learned from previous competitions and research. We present our vehicle and our approach to tackle the task of detecting and finding victims in search and rescue environments. Our approach contains known topics in robotics, such as ROS, SLAM, Human Robot Interaction and segmentation and perception. Our proposed approach is open source, available to the RoboCup Rescue community, where we aim to learn and contribute to the league.

Figures (10)

• Figure 1: Limo Robot for Competition Configuration.
• Figure 2: LIMO Mobile Robot: Standard Version.
• Figure 3: PincherX-100 Manipulator.
• Figure 4: NVIDIA Jetson Nano.
• Figure 5: Communication topology of the Limo Robot.