Microlidar Application for Object Detector to Support The Navigation System in Self-Driving Vehicle

Abstract

The ability to detect and measure the distance of potential obstacles is importance for navigation system in self-driving vehicles. The measurement process needs to be fast and accurate since the controller requires real-time data to make quick decisions and respond to any potential disturbances on the vehicle's track. This research aims to develop Microlidar for detection system that can accurately measure the distance of a potential obstacle object. The Microlidar utilize Lidar Lite V3 proximity sensor which have range measurement specification of up to 40 meter. Microlidar rapidly rotate 360 degrees by using a stepper motor while in the same time continuously measure the real-time distance. The measurement data are sent to a microcontroller through I2C, and the Processing software plot the 2D image which work like radar visualization. The system is assessed for ranging the various distance object in static and dynamic measurement mode. The results show that the Microlidar has a good level of accuracy with an average error value at the distance of 300 cm is 4.99 cm or 1.7% while the average error value at the distance of 1000 cm is 15.69 cm or 1.6% obtained from 100 data sets collected. The communication from the sensor to Arduino requires a minimum baud rate of 115200 bits/second to minimize data loss and ensure that the measured distance can be processed in real time by the microcontroller. Real-time data with high speed is essential since it will be used on the vehicle in order to quickly decide whether there is a barrier or not on the vehicle’s track. The sensor analysis distance expected from this research could be used as a reference to support the navigation system performance of self-driving vehicles.