In recent years, humanoid robots have gained significant attention due to their potential to
revolutionize various industries, from healthcare to manufacturing. A key factor driving this …

This article presents a team of multiple Unmanned Aerial Vehicles (UAVs) to perform
cooperative missions for autonomous construction. In particular, the UAVs have to build a …

Beating the human world champions by 2050 is an ambitious goal of the Humanoid League
that provides a strong incentive for RoboCup teams to further improve and develop their …

Detecting the field boundary is often one of the first steps in the vision pipeline of soccer
robots. Conventional methods make use of a (possibly adaptive) green classifier, selection …

Visually guided control of micro aerial vehicles (MAV) demands for robust real-time
perception, fast trajectory generation, and a capable flight platform. We present a fully …

Pose estimation commonly refers to computer vision methods that recognize people's body
postures in images or videos. With recent advancements in deep learning, we now have …

Abstract The RoboCup Humanoid League holds annual soccer robot world championships
towards the long-term objective of winning against the FIFA world champions by 2050. The …

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

In this paper, we propose a novel Deep Reinforcement Learning approach to address the
mapless navigation problem, in which the locomotion actions of a humanoid robot are taken …

Efficient and collision-free navigation is an essential requirement for deploying robots in
quotidian scenarios. In the robotics community, Reinforcement Learning (RL) approaches …