Titlebook: RoboCup 2018: Robot World Cup XXII; Dirk Holz,Katie Genter,Oskar von Stryk Conference proceedings 2019 Springer Nature Switzerland AG 2019

PALSY

Visual SLAM-Based Localization and Navigation for Service Robots: The Pepper Caseose short-range LIDARs and RGB-D camera do not allow the robot to self-localize in large environments. The localization system is tested in navigation tasks using Pepper in two different environments: a medium-size laboratory, and a large-size hall.

Incorporate

hemorrhage

ImageTagger: An Open Source Online Platform for Collaborative Image Labelingwhich facilitates creating and sharing such data sets. The tool is already being successfully used in RoboCup Soccer, and a large amount of labeled data is publicly available. Other leagues are invited to use this tool to create data for their contexts.

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0302-9743 .The 32 full revised papers and 11 papers from the winning teams presented were carefully reviewed and selected from 51 submissions. .This book highlights the approaches of champion teams from the competitions and documents the proceedings of the 22nd annual RoboCup International Symposium. Due to

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制造

End-to-End Deep Imitation Learning: Robot Soccer Case Studys of images and speed commands. In 3D realistic robotics simulator experiments, we show that the robot is able to learn to search the ball and dribble the ball, but it struggles to align to the goal. The best-proposed policy model learns to score 4 goals out of 20 test episodes.

condemn

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并置

Playing Soccer Without Colors in the SPL: A Convolutional Neural Network Approach system is tested in a SPL field with several NAO robots under realistic and highly demanding conditions. The obtained results are: robot detection rate of 94.90%, ball detection rate of 97.10%, and a completely perceived orientation rate of 99.88% when the observed robot is static, and 95.52% when the observed robot is moving.

nonchalance