论文标题
具有成本效益的两轮kian-i移动机器人的可行性评估用于自动导航
Feasibility Assessment of a Cost-Effective Two-Wheel Kian-I Mobile Robot for Autonomous Navigation
论文作者
论文摘要
在这项研究中,设计和原型设计了两轮的移动机器人,即kian-i。 Kian-I在维度规格,固定传感器和性能功能方面与Khepera-IV相当,可用于教育目的和具有成本效益的实验测试。在本研究中,为Kian-I设计了运动控制架构,以促进身临其境的机器人的准确导航。实现的控制结构由路径推荐系统和轨迹跟踪控制器的两个主要组成部分组成。给定有关操作场的部分知识,路径推荐系统采用B-Spline曲线和粒子群优化(PSO)算法来确定具有转换速度约束的无碰撞路径曲线。提供的最佳参考路径将馈入轨迹跟踪控制器,使Kian-I能够在操作领域自动导航。轨迹跟踪模块通过控制车轮的速度来消除所需路径和随后的轨迹之间的误差。为了评估拟议的控制体系结构的可行性,通过许多模拟和实验研究,可以评估Kian-I机器人在自主导航中从任何任意初始姿势到感兴趣的目标的性能的性能。实验结果证明了原型机器人的功能能力和性能,可作为实验室环境中各种移动机器人算法进行研究和验证的基准。
A two-wheeled mobile robot, namely Kian-I, is designed and prototyped in this research. The Kian-I is comparable with Khepera-IV in terms of dimensional specifications, mounted sensors, and performance capabilities and can be used for educational purposes and cost-effective experimental tests. A motion control architecture is designed for Kian-I in this study to facilitate accurate navigation for the robot in an immersive environment. The implemented control structure consists of two main components of the path recommender system and trajectory tracking controller. Given partial knowledge about the operation field, the path recommender system adopts B-spline curves and Particle Swarm Optimization (PSO) algorithm to determine a collision-free path curve with translational velocity constraint. The provided optimal reference path feeds into the trajectory tracking controller enabling Kian-I to navigate autonomously in the operating field. The trajectory tracking module eliminate the error between the desired path and the followed trajectory through controlling the wheels' velocity. To assess the feasibility of the proposed control architecture, the performance of Kian-I robot in autonomous navigation from any arbitrary initial pose to a target of interest is evaluated through numerous simulation and experimental studies. The experimental results demonstrate the functional capacities and performance of the prototyped robot to be used as a benchmark for investigation and verification of various mobile robot algorithms in the laboratory environment.