Real-time robot motion planning using rasterizing computer graphics hardware
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
Introduction to the theory of neural computation
Introduction to the theory of neural computation
Robot Motion Planning
Machine Learning
Agilo RoboCuppers: RoboCup Team Description
RoboCup 2000: Robot Soccer World Cup IV
Reliable Multi-robot Coordination Using Minimal Communication and Neural Prediction
Revised Papers from the International Seminar on Advances in Plan-Based Control of Robotic Agents,
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In this paper we propose a hybrid navigation planning and execution system for performing joint navigation tasks in autonomous robot soccer. The proposed system consists of three components: an artificial neural network controller, a library of software tools for planning and plan merging, and a decision module that selects the appropriate planning and execution methods in a situation-specific way. The system learns by experimentation predictive models for the performance of different navigation planning methods. The decision module uses the learned predictive models to select the most promising planning method for the given navigation task.In extensive experiments using a realistic and accurate robot simulator that has learned the dynamic model of the real robots we show that our navigation system is capable to (1) generate fast and smooth navigation trajectories and (2) outperform the state of the art planning methods.