以飞思卡尔杯全国大学生智能车竞赛为背景，研究了电磁式智能车如何从有限的道路信息中提取车身与实际跑道中心的偏差. 传统的计算方法是根据左右两个电感的电压值进行差值计算或者是归一化计算以此得到一个数值表示车体中心偏离跑道中心的程度. 但是这些算法计算出来偏差都存在不够线性的弊端，对于需要依靠偏差来进行车体舵机转角和电机加减速的智能车控制系统来讲这是一个很大的问题. 本文提出一种新的计算方法，从理论上通过Maple仿真证明了能够解决归一化算法和差值算法的弊端. 通过实验证实算法的可行性.;The Freescale Cup National Undergraduate Smart Car Competition for the background, how electromagnetic smart car road information from the limited body to extract the deviation from the actual center of the runway. Traditional method is based around two inductive voltage value or the difference calculating a normalized value calculated in order to obtain a deviation from the track center of said body center level. However, these algorithms are present enough deviation calculated from linear defects, the need to rely on steering angle deviation for the body and the motor acceleration and deceleration of the intelligent vehicle control system is concerned this is a big problem. This paper presents a new method of calculating theoretically proved through simulation Maple normalization algorithm to solve the difference algorithm and drawbacks. By applying this algorithm to the actual competition, which validate the algorithm.
2021-09-19 17:37:44
692KB
1