SUMMARYThis paper emphasizes on Bacterial Foraging Optimization Algorithm for effective and efficient navigation of humanoid NAO, which uses the foraging quality of bacteria Escherichia coli for getting shortest path between two locations in minimum time. The Gaussian cost function assigned to both attractant and repellent profile of bacterium performs a major role in obtaining the best path between any two locations. Mathematical formulations have been performed to design the control architecture for humanoid navigation using the proposed methodology. The developed approach has been tested in a simulation platform, and the simulation results have been validated in an experimental platform. Here, motion planning for both single and multiple humanoid robots on a common platform has been performed by integrating a petri-net architecture for multiple humanoid navigation. Finally, the results obtained from both the platforms are compared in terms of suitable navigational parameters, and proper agreements have been observed with minimal amount of error limits.

中文翻译：

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使用细菌觅食优化改进仿人机器人的运动规划

摘要本文重点介绍了细菌觅食优化算法，用于人形NAO的有效导航，该算法利用细菌的觅食质量大肠杆菌在最短的时间内获得两个位置之间的最短路径。分配给细菌的引诱剂和驱虫剂轮廓的高斯成本函数在获得任何两个位置之间的最佳路径方面发挥着重要作用。使用所提出的方法，已经执行了数学公式来设计人形导航的控制架构。所开发的方法已经在仿真平台上进行了测试，仿真结果在实验平台上得到了验证。在这里，通过集成用于多个人形导航的 petri-net 架构，在一个公共平台上对单个和多个人形机器人进行了运动规划。最后，从两个平台获得的结果在合适的导航参数方面进行了比较，