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An Improved Ant-Driven Approach to Navigation and Map Building

机译:一种改进的蚂蚁驱动的导航和地图构建方法

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An improved ant-type approach, ant colony optimization (ACO) model, integrated with a heading direction scheme (HDS) to real-time collision-free navigation and mapping of an autonomous robot is proposed in this paper. The developed HDS-based ACO model for concurrent map building and safety-aware navigation is capable of remedying the shortcoming of risky distance from obstacles in combination with the Dynamic Window Approach (DWA) algorithm as a local navigator. Its effectiveness and efficiency of the developed real-time hybrid map building and safety-aware navigation of an autonomous robot have been successfully validated by simulated experiments and comparison studies.
机译:提出了一种改进的蚁群算法,蚁群优化(ACO)模型,与航向方向方案(HDS)相集成,实现了自主机器人的实时无碰撞导航和制图。结合动态窗口方法(DWA)算法作为本地导航器,针对并发地图构建和安全意识导航而开发的基于HDS的ACO模型能够弥补与障碍物之间的危险距离的缺点。通过仿真实验和比较研究,已成功验证了其开发的实时混合地图构建和自主机器人的安全意识导航的有效性和效率。

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