Abstract

Science and technology at this time are developing so rapidly. Accuracy, effectiveness, and efficiency are the main things offered with the development of technology. One form of this aspect is the creation of an automatic randomization system of an object with a mobile robot system. This study aims to produce a mobile robot prototype for object tracking that utilizes sensor vision as the main component in tracking an object, where the system built can distinguish an object based on color and can approach the object automatically because in this robot an autonomous mobile robot system is applied. In this research, it combines two main components, namely hard components and soft components. The hard components are composed of the Pixy CMU Cam5 as a sensor vision to recognize objects that have been targeted, the DC motor is used as a robotic locomotor to approach the intended object, the L298N Driver Shield Motor as the DC motor processing of the microcontroller, and Arduino UNO as the main microcontroller in the mobile robot tracking object prototype. The soft components consist of the PixyMon application which is used for the process of configuring digital images of color-based objects and the Arduino IDE which is used to write robotic movement system programs when they have recognized objects which are then uploaded into the microcontroller. As a result of the tests that have been carried out, the DC motor can move according to the specifications that have been made and the pixy sensor vision can capture pixels of well-configured colors.

Keywords:
Computer science Computer vision Mobile robot Artificial intelligence Microcontroller Robot Object (grammar) Process (computing) Arduino Video tracking Tracking system Machine vision Camera module Computer hardware Embedded system Kalman filter

Metrics

3
Cited By
0.32
FWCI (Field Weighted Citation Impact)
14
Refs
0.55
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

IoT-based Smart Home Systems
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Water Quality Monitoring Technologies
Physical Sciences →  Environmental Science →  Water Science and Technology
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