To shorten the convergence time, the optimal search problem of disparity map is converted to an iterative convergence process of bi-valued neural networks.
为加快收敛速度,该算法将视差图的最优搜索问题转换为二值神经网络的迭代收敛过程。
And through compare with non-Evolutionary Map building method, the Evolutionary Reinforcement learning algorithm can increase search map efficiency and expedite convergence speed of global map.
通过与非进化模式下的多机器人地图构建方法的比较,该算法可以提高地图搜索的效率,加快全局地图的收敛。
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