Self-organizing robot formations using velocity potential fields commands for material transfer

using game theory techniques in self-organizing maps training

شبکه خود سازمانده پرکاربردترین شبکه عصبی برای انجام خوشه بندی و کوانتیزه نمودن برداری است. از زمان معرفی این شبکه تاکنون، از این روش در مسائل مختلف در حوزه های گوناگون استفاده و توسعه ها و بهبودهای متعددی برای آن ارائه شده است. شبکه خودسازمانده از تعدادی سلول برای تخمین تابع توزیع الگوهای ورودی در فضای چندبعدی استفاده می کند. احتمال وجود سلول مرده مشکلی اساسی در الگوریتم شبکه خودسازمانده به حسا...

Local Autonomous Robot Navigation using Potential Fields

The potential fields method for autonomous robot navigation consists essentially in the assignment of an attractive potential to the goal point and a repulsive potential to each of the obstacles in the environment. Several implementations of potential fields for autonomous robot navigation have been reported. The most simple implementation considers a known environment where fixed potentials ca...

Adaptive Sliding Mode Tracking Control of Mobile Robot in Dynamic Environment Using Artificial Potential Fields

Solution to the safe and collision-free trajectory of the wheeled mobile robot in cluttered environments containing the static and/or dynamic obstacle has become a very popular and challenging research topic in the last decade. Notwithstanding of the amount of publications dealing with the different aspects of this field, the ongoing efforts to address the more effective and creative methods is...

Self-Organizing Dynamic Neural Fields

In this paper, we propose a model of cortical self-organization based on the dynamic field theory. Learning is made through the modification of feed-forward connections using a time invariant learning rule that allows for dynamic (or life-long) learning. This preliminary model suggests that cortical plasticity may be conveyed through feed-forward connections only while cortico-cortical connecti...

Forward Chaining for Robot and Agent Navigation using Potential Fields