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

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书目名称RoboCup 2018: Robot World Cup XXII影响因子(影响力)




书目名称RoboCup 2018: Robot World Cup XXII影响因子(影响力)学科排名




书目名称RoboCup 2018: Robot World Cup XXII网络公开度




书目名称RoboCup 2018: Robot World Cup XXII网络公开度学科排名




书目名称RoboCup 2018: Robot World Cup XXII被引频次




书目名称RoboCup 2018: Robot World Cup XXII被引频次学科排名




书目名称RoboCup 2018: Robot World Cup XXII年度引用




书目名称RoboCup 2018: Robot World Cup XXII年度引用学科排名




书目名称RoboCup 2018: Robot World Cup XXII读者反馈




书目名称RoboCup 2018: Robot World Cup XXII读者反馈学科排名

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Multi-Robot Fast-Paced Coordination with Leader Electioncan efficiently achieve their pre-defined global objective. From a wide range of multi-agent coordination sub-topics, one of the current open issues is task assignment and role selection in fast-paced environments. In homogeneous teams, where robots have the ability to dynamically change roles, work

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Visual Mesh: Real-Time Object Detection Using Constant Sample Densityansformation called Visual Mesh. It uses object geometry to create a graph in vision space, reducing computational complexity by normalizing the pixel and feature density of objects. The experiments compare the Visual Mesh with several other fast convolutional neural networks. The results demonstrat

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Learning Skills for Small Size League RoboCuphitecture. STP divides the robot behavior into a hand-coded hierarchy of plays, which coordinate multiple robots, tactics, which encode high level behavior of individual robots, and skills, which encode low-level control of pieces of a tactic. The CMDragons successfully used an STP architecture to w

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Real-Time Scene Understanding Using Deep Neural Networks for RoboCup SPL platforms is challenging because of CNNs’ excessive computational requirements. We present an end-to-end neural network solution to scene understanding for robot soccer. We compose two key neural networks: one to perform semantic segmentation on an image, and another to propagate class labels betwe

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Training a RoboCup Striker Agent via Transferred Reinforcement Learningtion spaces with continuous parameters. Advancements such as the Deep-Q Network and the Deep Deterministic Policy Gradient were a critical step in making reinforcement learning a feasible option for training agents in real world scenarios. The viability of these technologies has previously been demo

Intruder

Playing Soccer Without Colors in the SPL: A Convolutional Neural Network Approachstem are: (i) real-time operation in the NAO robot, and (ii) the ability to detect the ball, the robots, their orientations, the lines and key field features robustly. Our ball detector, robot detector, and robot’s orientation detector obtain the highest reported detection rates. The proposed vision