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Path planning and trajectroy tracking of a mobile robot using bio-inspired optimization algorithms and PID control

机译:利用生物启发式优化算法和PID控制的移动机器人路径规划和轨迹跟踪

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Path planning and trajectory tacking are the fundamental task in mobile robotic science, and they enable the robot to navigate autonomously. In this work, the path planning task is carried out using three bio-inspired optimization algorithms, including PSO, ABC and FA. The duty of the algorithms is to determine a collision-free path through fixed obstacles in the working environment. The maximum speed of the robot is applied to the optimization problem as a constraint. In order to evaluate the performance of the algorithms, four workspaces with different obstacle layout are simulated in MATLAB, and the quality of path planning task is analyzed statistically and numerically, considering four different criteria, including, convergency quality, convergency time, path length and success rate. In the next step, a control model is designed to track the path curve determined by the path planning algorithms. A PID-based control structure is simulated in MATLAB Simulink and the controller was able to track the pre-determined traj ectories with proper approximation. The controller is applied on a dynamic model of a two-wheeled mobile robot offered by [1]. In order to validate the control inputs it is necessary to apply them on a real platform. The experimental study is implemented on a two-wheeled mobile robot which is designed and built based on the authors' previous paper [2] in various enverioment and obstacles. The result shows control inputs were applied to the real robot and the robot was able to imitate the applied path curve, and find its way toward the target point without colliding obstacles in real and simulation task.
机译:路径规划和轨迹追踪是移动机器人科学的基本任务,它们使机器人能够自主导航。在这项工作中,路径规划任务是使用三种受生物启发的优化算法(包括PSO,ABC和FA)执行的。算法的职责是确定在工作环境中穿过固定障碍物的无碰撞路径。机器人的最大速度作为约束条件应用于优化问题。为了评估算法的性能,在MATLAB中模拟了四个具有不同障碍物布局的工作空间,并考虑了四个不同的标准,包括收敛质量,收敛时间,路径长度和路径长度,对路径规划任务的质量进行了统计和数字分析。成功率。在下一步中,将设计一个控制模型来跟踪由路径规划算法确定的路径曲线。在MATLAB Simulink中对基于PID的控制结构进行了仿真,该控制器能够以适当的近似值跟踪预定轨迹。该控制器应用于[1]提供的两轮移动机器人的动力学模型。为了验证控制输入,有必要在真实平台上应用它们。实验研究是在两轮移动机器人上进行的,该机器人是根据作者先前的论文[2]在各种环境和障碍下设计和建造的。结果表明,将控制输入应用于真实机器人,并且该机器人能够模仿所应用的路径曲线,并在不碰到实际和模拟任务中的障碍的情况下找到其向目标点的路径。

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