Bold Hearts Team Description for RoboCup 2019 (Humanoid Kid Size League)

We participated in the RoboCup 2018 competition in Montreal with our newly developed BoldBot based on the Darwin-OP and mostly self-printed custom parts. This paper is about the lessons learnt from that competition and further developments for the RoboCup 2019 competition. Firstly, we briefly introduce the team along with an overview of past achievements. We then present a simple, standalone 2D simulator we use for simplifying the entry for new members with making basic RoboCup concepts quickly accessible. We describe our approach for semantic-segmentation for our vision used in the 2018 competition, which replaced the lookup-table (LUT) implementation we had before. We also discuss the extra structural support we plan to add to the printed parts of the BoldBot and our transition to ROS 2 as our new middleware. Lastly, we will present a collection of open-source contributions of our team.Comment: Technical repor

Trends, Challenges and Adopted Strategies in RoboCup@Home (2019 version)

Scientific competitions are crucial in the field of service robotics. They foster knowledge exchange and benchmarking, allowing teams to test their research in unstandardized scenarios. In this paper, we summarize the trending solutions and approaches used in RoboCup@Home. Further on, we discuss the attained achievements and challenges to overcome in relation with the progress required to fulfill the long-term goal of the league. Consequently, we propose a set of milestones for upcoming competitions by considering the current capabilities of the robots and their limitations. With this work we aim at laying the foundations towards the creation of roadmaps that can help to direct efforts in testing and benchmarking in robotics competitions.Comment: 7 pages, 4 figures, 3 tables. Accepted paper to be presented and published in the 2019 IEEE International Conference on Autonomous Robot Systems and Competitions. arXiv admin note: substantial text overlap with arXiv:1903.0251

RoboCup 2016 Humanoid TeenSize Winner NimbRo: Robust Visual Perception and Soccer Behaviors

The trend in the RoboCup Humanoid League rules over the past few years has been towards a more realistic and challenging game environment. Elementary skills such as visual perception and walking, which had become mature enough for exciting gameplay, are now once again core challenges. The field goals are both white, and the walking surface is artificial grass, which constitutes a much more irregular surface than the carpet used before. In this paper, team NimbRo TeenSize, the winner of the TeenSize class of the RoboCup 2016 Humanoid League, presents its robotic platforms, the adaptations that had to be made to them, and the newest developments in visual perception and soccer behaviour.Comment: RoboCup 2016: Robot World Cup XX, Lecture Notes in Computer Science 9776, Springer, 201

Humanoid TeenSize Open Platform NimbRo-OP

In recent years, the introduction of affordable platforms in the KidSize class of the Humanoid League has had a positive impact on the performance of soccer robots. The lack of readily available larger robots, however, severely affects the number of participants in Teen- and AdultSize and consequently the progress of research that focuses on the challenges arising with robots of larger weight and size. This paper presents the first hardware release of a low cost Humanoid TeenSize open platform for research, the first software release, and the current state of ROS-based software development. The NimbRo-OP robot was designed to be easily manufactured, assembled, repaired, and modified. It is equipped with a wide-angle camera, ample computing power, and enough torque to enable full-body motions, such as dynamic bipedal locomotion, kicking, and getting up.Comment: Proceedings of 17th RoboCup International Symposium, Eindhoven, Netherlands, 201

Advanced Soccer Skills and Team Play of RoboCup 2017 TeenSize Winner NimbRo

In order to pursue the vision of the RoboCup Humanoid League of beating the soccer world champion by 2050, new rules and competitions are added or modified each year fostering novel technological advances. In 2017, the number of players in the TeenSize class soccer games was increase to 3 vs. 3, which allowed for more team play strategies. Improvements in individual skills were also demanded through a set of technical challenges. This paper presents the latest individual skills and team play developments used in RoboCup 2017 that lead our team Nimbro winning the 2017 TeenSize soccer tournament, the technical challenges, and the drop-in games.Comment: In Proceedings of 21th RoboCup International Symposium, Nagoya, Japa

Trends, Challenges and Adopted Strategies in RoboCup@Home

Scientific competitions are crucial in the field of service robotics. They foster knowledge exchange and allow teams to test their research in unstandardized scenarios and compare result. Such is the case of RoboCup@Home. However, keeping track of all the technologies and solution approaches used by teams to solve the tests can be a challenge in itself. Moreover, after eleven years of competitions, it's easy to delve too much into the field, losing perspective and forgetting about the user's needs and long term goals. In this paper, we aim to tackle this problems by presenting a summary of the trending solutions and approaches used in RoboCup@Home, and discussing the attained achievements and challenges to overcome in relation with the progress required to fulfill the long-term goal of the league. Hence, considering the current capabilities of the robots and their limitations, we propose a set of milestones to address in upcoming competitions. With this work we lay the foundations towards the creation of roadmaps that can help to direct efforts in testing and benchmarking in robotics competitions.Comment: 18 pages, 7 figures, 3 table

SIGVerse: A cloud-based VR platform for research on social and embodied human-robot interaction

Common sense and social interaction related to daily-life environments are considerably important for autonomous robots, which support human activities. One of the practical approaches for acquiring such social interaction skills and semantic information as common sense in human activity is the application of recent machine learning techniques. Although recent machine learning techniques have been successful in realizing automatic manipulation and driving tasks, it is difficult to use these techniques in applications that require human-robot interaction experience. Humans have to perform several times over a long term to show embodied and social interaction behaviors to robots or learning systems. To address this problem, we propose a cloud-based immersive virtual reality (VR) platform which enables virtual human-robot interaction to collect the social and embodied knowledge of human activities in a variety of situations. To realize the flexible and reusable system, we develop a real-time bridging mechanism between ROS and Unity, which is one of the standard platforms for developing VR applications. We apply the proposed system to a robot competition field named RoboCup@Home to confirm the feasibility of the system in a realistic human-robot interaction scenario. Through demonstration experiments at the competition, we show the usefulness and potential of the system for the development and evaluation of social intelligence through human-robot interaction. The proposed VR platform enables robot systems to collect social experiences with several users in a short time. The platform also contributes in providing a dataset of social behaviors, which would be a key aspect for intelligent service robots to acquire social interaction skills based on machine learning techniques.Comment: 16 pages. Under review in Frontiers in Robotics and A

NimbRo-OP2: Grown-up 3D Printed Open Humanoid Platform for Research

The versatility of humanoid robots in locomotion, full-body motion, interaction with unmodified human environments, and intuitive human-robot interaction led to increased research interest. Multiple smaller platforms are available for research, but these require a miniaturized environment to interact with---and often the small scale of the robot diminishes the influence of factors which would have affected larger robots. Unfortunately, many research platforms in the larger size range are less affordable, more difficult to operate, maintain and modify, and very often closed-source. In this work, we introduce NimbRo-OP2X, an affordable, fully open-source platform in terms of both hardware and software. Being almost 135cm tall and only 18kg in weight, the robot is not only capable of interacting in an environment meant for humans, but also easy and safe to operate and does not require a gantry when doing so. The exoskeleton of the robot is 3D printed, which produces a lightweight and visually appealing design. We present all mechanical and electrical aspects of the robot, as well as some of the software features of our well-established open-source ROS software. The NimbRo-OP2X performed at RoboCup 2017 in Nagoya, Japan, where it won the Humanoid League AdultSize Soccer competition and Technical Challenge.Comment: International Conference on Humanoid Robots (Humanoids), Birmingham, England, 201

A ROS-based Software Framework for the NimbRo-OP Humanoid Open Platform

Over the past few years, a number of successful humanoid platforms have been developed, including the Nao and the DARwIn-OP, both of which are used by many research groups for the investigation of bipedal walking, full-body motions, and human-robot interaction. The NimbRo-OP is an open humanoid platform under development by team NimbRo of the University of Bonn. Significantly larger than the two aforementioned humanoids, this platform has the potential to interact with a more human-scale environment. This paper describes a software framework for the NimbRo-OP that is based on the Robot Operating System (ROS) middleware. The software provides functionality for hardware abstraction, visual perception, and behavior generation, and has been used to implement basic soccer skills. These were demonstrated at RoboCup 2013, as part of the winning team of the Humanoid League competition.Comment: Proceedings of 8th Workshop on Humanoid Soccer Robots, International Conference on Humanoid Robots (Humanoids), Atlanta, USA, 201

A Monocular Vision System for Playing Soccer in Low Color Information Environments

Humanoid soccer robots perceive their environment exclusively through cameras. This paper presents a monocular vision system that was originally developed for use in the RoboCup Humanoid League, but is expected to be transferable to other soccer leagues. Recent changes in the Humanoid League rules resulted in a soccer environment with less color coding than in previous years, which makes perception of the game situation more challenging. The proposed vision system addresses these challenges by using brightness and texture for the detection of the required field features and objects. Our system is robust to changes in lighting conditions, and is designed for real-time use on a humanoid soccer robot. This paper describes the main components of the detection algorithms in use, and presents experimental results from the soccer field, using ROS and the igus Humanoid Open Platform as a testbed. The proposed vision system was used successfully at RoboCup 2015.Comment: Proceedings of 10th Workshop on Humanoid Soccer Robots, International Conference on Humanoid Robots (Humanoids), Seoul, Korea, 201