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An Effective Track Designing Approach for a Mobile Robot

机译:一种有效的移动机器人轨道设计方法

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Advancements of technology in day to day life demands upgradation in the existing soft computing approaches, for enhancing the accuracy. So, the existing particle swarm optimization (PSO) has been upgraded in this article and the new approach is adaptive particle swarm optimization (APSO). Designing an effective track which is shorter in length, takes less travel time, computation time, smooth, feasible and has zero collision risk with obstacles is always a crucial issue. To solve these issues APSO approach has been adopted in this work. A static environment has been implemented in this article for conducting the simulation study. Fifteen numbers of obstacles have been taken into consideration for designing the environment. A comparability study has been stuck between PSO and APSO to recognize the fittest approach for track design (less track size and travel time) with the shortest computation time. The APSO approach is identified as the best suited track designing tool for mobile robots.
机译:日常生活中技术的进步要求对现有的软计算方法进行升级,以提高准确性。因此,本文对现有的粒子群优化(PSO)进行了升级,而新方法是自适应粒子群优化(APSO)。设计一条长度短,行进时间短,计算时间短,平滑,可行并且与障碍物的碰撞风险为零的有效轨道始终是关键问题。为了解决这些问题,这项工作采用了APSO方法。本文已实现了静态环境以进行仿真研究。在设计环境时已考虑了十五个障碍。 PSO和APSO之间进行了可比性研究,目的是要以最短的计算时间来确定最合适的轨道设计方法(较小的轨道尺寸和行进时间)。 APSO方法被认为是最适合移动机器人的轨道设计工具。

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