Robotics researchers have been focusing on developing autonomous and human-like
intelligent robots that are able to plan, navigate, manipulate objects, and interact with …

Fast and accurate visual perception utilizing a robot's limited hardware resources is
necessary for many mobile robot applications. We are presenting YOEO, a novel hybrid …

This research aims to enhance humanoid robot soccer Ball Tracking, Goal Alignment, and
Robot avoidance tasks using YOLO-NAS. The study followed a three-stage approach …

We showcase a pipeline to train, evaluate, and deploy deep learning architectures for
monocular depth estimation in the RoboCup Soccer Humanoid domain. In contrast to …

The humanoid robot soccer system encounters a notable challenge in object detection,
primarily concentrating on identifying the ball and often neglecting crucial elements like …

This paper proposes a method to calibrate the model used for inverse perspective mapping
of humanoid robots. It aims at providing a reliable way to determine the robot's position …

This paper presents a vision system for ball detection and tracking in the context of the
RoboCup Soccer Humanoid League Kidsize category. The system aims to enable …

In this extended abstract, we present new software approaches and hardware developments
since RoboCup 2019. We present valuable lessons learned from our participation in the last …

This thesis investigates the learning of motion skills for humanoid robots. As groundwork, a
humanoid robot with integrated fall management was developed as an experimental …

In this thesis, multiple deep active learning methods are compared and evaluated for their
use in the RoboCup soccer domain on the TORSO-21 dataset. The manual annotating of …