This paper proposes the right and left motor velocity based multi-objective genetic algorithm controlled navigation method for Two-Wheeled Pioneer P3-DX Robot (TWPR) in Virtual Robot Experimentation Platform (V-REP) software scenarios. The first objective function is made by taking front, left, and right ultrasonic sensors data and right motor velocity. Similarly, the second objective function is designed using front, left, and right ultrasonic sensors data and left motor velocity. Next, the sensor data are considered independent variables or inputs. The velocities of the motors are chosen as dependent variables or outputs for making multi-objective fitness functions for genetic algorithm (GA). This multi-objective GA makes a sensor-actuator control architecture and helps the TWPR to avoid the obstacles in the simulated scenarios. Further, the successful simulation test results show that the multi-objective GA provided a collision-free smooth, and shortest path for TWPR compared to the previously developed benchmark single objective GA.

本文提出了基于左右电机速度的多目标遗传算法控制的双轮先锋P3-DX机器人（TWPR）在虚拟机器人实验平台（V-REP）软件场景中的导航方法。第一个目标函数是通过取前、左、右超声波传感器数据和右电机速度来制作的。同样，第二个目标函数是使用前、左、右超声波传感器数据和左电机速度设计的。接下来，传感器数据被视为独立变量或输入。电机的速度被选为因变量或输出，用于为遗传算法 (GA) 制作多目标适应度函数。这种多目标 GA 构成了传感器-执行器控制架构，并帮助 TWPR 避开模拟场景中的障碍物。更多，