UruBots RoboCup Work Team Description Paper

TL;DR

The paper addresses enabling autonomous operation of mobile robots in industrial work environments for RoboCup@Work by presenting a hardware–software stack built around the Limo platform, integrating a Jetson Nano, LiDAR, depth camera, and a ROBOTIS OpenManipulator-X within a ROS1 Melodic framework. The software architecture fuses Cartographer-based SLAM, AprilTag-based perception, and a ROS-driven task planner to coordinate navigation, perception, and manipulation. A qualification experiment in a controlled 5x5 m arena demonstrates autonomous mapping, docking, object detection and grasping, and object relocation, validating the integrated system. The work advances readiness for RoboCup@Work and industrial human–robot interaction scenarios, with future plans to incorporate YOLO-based perception for untagged objects and to refine planning and perception for richer tasks.

Abstract

This work presents a team description paper for the RoboCup Work League. Our team, UruBots, has been developing robots and projects for research and competitions in the last three years, attending robotics competitions in Uruguay and around the world. In this instance, we aim to participate and contribute to the RoboCup Work category, hopefully making our debut in this prestigious competition. For that, we present an approach based on the Limo robot, whose main characteristic is its hybrid locomotion system with wheels and tracks, with some extras added by the team to complement the robot's functionalities. Overall, our approach allows the robot to efficiently and autonomously navigate a Work scenario, with the ability to manipulate objects, perform autonomous navigation, and engage in a simulated industrial environment.

Figures (9)

• Figure 1: Proposed Robotic Platform.
• Figure 2: Nvidia Jetson Nano. Nano
• Figure 3: Communication topology of the Limo Robot.
• Figure 4: ROBOTIS OpenManipulator-X robotis-open.
• Figure 5: ORBBEC Dabai Deep Camera.