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Obstacle Avoidance Method Based on Multi-source Information Fusion Intended for Robots Operating in Different Environments

机译:基于多源信息融合的障碍避免方法,用于在不同环境中运行的机器人

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Obstacle avoidance is a precondition for a smooth robot moving. However, current methods for obstacle avoidance are deficient in different information and sensitive to environmental conditions. In order to overcome the two mentioned shortcomings, this paper proposes an automatic obstacle avoidance method based on multi-source information fusion. A multi-source information platform is constructed based on the multi-core embedded system, and an artificial intelligence algorithm is used to construct the environment factor acquisition model. Also, a multi-source information fusion method based on fuzzy theory is proposed. Finally, a prototype test platform is constructed to conduct practical experiments on obstacle avoidance for different environments. Experimental results show that the presented method has the advantage of high obstacle identification rate.
机译:避免避免是平滑机器人移动的前提。然而,避免障碍物的当前方法缺乏不同的信息和对环境条件敏感。为了克服两种提到的缺点,本文提出了一种基于多源信息融合的自动避障方法。基于多核嵌入式系统构建多源信息平台,使用人工智能算法来构造环境因子采集模型。此外,提出了一种基于模糊理论的多源信息融合方法。最后,构建了原型测试平台,以对不同环境的障碍避免进行实际实验。实验结果表明,呈现的方法具有高障碍率识别率的优点。

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