Evolutionary gait-optimization using a fitness function based on proprioception

Abstract. This paper presents a new approach to optimize gait parameter sets using evolutionary algorithms. It separates the crossover-step of the evolutionary algorithm into an interpolating step and an extrapolating step, which allows for solving optimization problems with a small population, which is an essential for robotics applications. In contrast to other approaches, odometry is used to assess the quality of a gait. Thereby, omni-directional gaits can be evolved. Some experiments with the Sony Aibo models ERS-210 and ERS-7 prove the performance of the approach including the fastest gait found so far for the Aibo ERS-210.

ROS 2 for RoboCup

There has always been much motivation for sharing code and solutions among teams in the RoboCup community. Yet the transfer of code between teams was usually complicated due to a huge variety of used frameworks and their differences in processing sensory information. The RoboCup@Home league has tackled this by transitioning to ROS as a common framework. In contrast, other leagues, such as those using humanoid robots, are reluctant to use ROS, as in those leagues real-time processing and low-computational complexity is crucial. However, ROS 2 now offers built-in support for real-time processing and promises to be suitable for embedded systems and multi-robot systems. It also offers the possibility to compose a set of nodes needed to run a robot into a single process. This, as we will show, reduces communication overhead and allows to have one single binary, which is pertinent to competitions such as the 3D-Simulation League. Although ROS 2 has not yet been announced to be production ready, we started the process to develop ROS 2 packages for using it with humanoid robots (real and simulated). This paper presents the developed modules, our contributions to ROS 2 core and RoboCup related packages, and most importantly it provides benchmarks that indicate that ROS 2 is a promising candidate for a common framework used among leagues

Efficient localization for robot soccer using pattern matching

One of the biggest challenges in the RoboCup Soccer Standard Platform League (SPL) is autonomously achieving and maintaining an accurate estimate of a robot’s position and orientation on the field. In other robotics applications many robust systems already exist for localization such as visual simultaneous localization and mapping (SLAM) and LIDAR based SLAM. These approaches either require special hardware or are very computationally expensive and are not suitable for the Nao robot, the current robot of choice for the SPL. Therefore novel approaches to localization in the RoboCup SPL environment are required. In this paper we present a new approach to localization in the SPL which relies primarily on the information contained within white field markings while being efficient enough to run in real time on board a Nao robot

Real-time Simulation of Motion-based Camera Disturbances

Abstract. In the RoboCup domain, many robot systems use low-cost image sensors to perceive the robot’s environment and to locate the robot in its environment. The image processing typically has to handle image distortions such as motion blur, noise, and the properties of the shutter mechanism. If a simulator is used in the development of the control software, the simulation has to take account for these artifacts. Otherwise, the performance of the image processing system in the simulation may not correspond to its performance on the real robot; it may even perform worse. The effect of motion blur has been widely used for special effects both for movies and for computer games. While real-time algorithms using modern graphics hardware came up in recent years, the image distortion resulting from a so-called rolling shutter has not been in focus so far. In fact, this effect is not relevant for gaming, but it is for simulating low-cost cameras of robots. In this paper, we present an efficient way to simulate the rolling shutter effect using per-pixel velocities. In addition, we improve the velocity buffer method for creating motion blur using the current speed of each pixel in real-time. The application of our approach is shown exemplarily for the head-mounted camera of a humanoid soccer robot.

A New Video Rate Region Color Segmentation and Classification for Sony Legged RoboCup Application

International audienc

GermanTeam 2001

The GermanTeam is the successor of the Humboldt Heroes who already participated in the Sony Legged Robot League competitions in 1999 and 2000. Because of the strong interest of other German universities, in March 2001, the GermanTeam was founded. It consists of students and researchers of five universities: Humboldt-Universität zu Berlin, Universität Bremen, Technische Universität Darmstadt, Universität Dortmund, and Freie Universität Berlin. However, for the system presented in this document, the Humbold Heroes only had reinforcements from Bremen and Darmstadt. The two other universities will actively participate with the beginning of the winter semester