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A coupled reaction-diffusion field model for perception-action cycle with applications to robot navigation

Eugene Aidman, Vladimir G. Ivancevic, Andrew Jennings

发表年份
2008
引用次数
5

摘要

A generalised reaction-diffusion field model for robot navigation is proposed. It utilises two mutually antagonistic neural fields counteracting in patterns similar to that of flexor/extensor muscles controlling the movements in major joints in the human body. Combining local activation and generalised inhibition represented by Amari's neural field equations and extended by the Fitzhugh-Nagumo and Wilson-Cowan activator-inhibitor systems, results in the type of neural attractor dynamics that may lead to spontaneous oscillatory pattern formation. Preliminary simulation data suggest that this approach has utility in enabling a team of autonomous vehicles to navigate in a crowded pedestrian crossing.

关键词

AttractorRobotArtificial neural networkReaction–diffusion systemComputer sciencePerceptionAction (physics)Potential fieldSimulationArtificial intelligence

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