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Eko Setiawan, Aan
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Navigation System using Single Camera with Fuzzy Logic Control and Obstacle Avoidance Adi Saputra, Angga Juliat; Rusdinar, Angga; Rizal, Syamsul; Rahayu, Eko; Eko Setiawan, Aan
eProceedings of Engineering Vol. 10 No. 5 (2023): Oktober 2023
Publisher : eProceedings of Engineering

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Abstract— Mobile Robot is a system that is able to perform or navigate intelligently using sensor actuator control techniques. Currently the Mobile Robot system is developing rapidly in various fields and research on it is increasingly being carried out. The research that has been done aims to find an efficient navigation system to be applied to the Mobile Robot system. In its application the navigation system on the Mobile Robot uses one or more sensors embedded in the Mobile Robot. This can lead to inefficiencies in terms of computing and in terms of making decisions in navigating the Mobile Robot. In the navigation system on the Mobile Robot, simplification of the use of sensors and computing can be made. By using Sensor Vision, namely the camera and performing centralized computing, it can create a time- and memory-efficient navigation system. The use of Sensor Vision is to replace the sensor which is usually implanted directly on the Mobile Robot to recognize or read the Mobile Robot’s working environment properly. The data that will be obtained from environmental readings are in the form of robot coordinates, goals, and obstacles using Object Detection. By computing centrally, the data will be processed with a Personal Computer (PC) using the Fuzzy Logic Control method, so that the Mobile Robot will only receive data in the form of right and left wheel speeds.Keywords— Mobile Robot, Object Detection, Sensor Vision, Obstacle, Fuzzy Logic Control
Computer Vision-Based Object Identification And Handling System: Case Study of KRSRI Robot (Indonesian Search And Rescue Robot Competition) Naufalfalah, Tamim; Castrena Abadi, Sarosa; Eko Setiawan, Aan
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 20 No. 2 (2026)
Publisher : Faculty of Engineering, Universitas Brawijaya

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Search And Rescue (SAR) robots are designed to locate and rescue victims from disaster sites to safe zones. In the 2024 Indonesian Search And Rescue Robot Contest (KRSRI), to earn points during rescue missions, the robot must identify victims among dummies with the victim oriented at a 45° angle and accurately place them in the safe zone. This research utilizes input from an Arducam camera and leverages the YOLOv4-Tiny Computer Vision algorithm, which offers reliable and adaptive detection and recognition capabilities under varying victim rescue conditions. The system outputs control commands for the robot's movement and manipulator arm. The final project successfully implemented the YOLOv4-Tiny model on a SAR robot, achieve real-time object detection at a minimum light intensity of 6 lux and a maximum distance of 60 cm. The system demonstrated a mAP of 99% and an IoU rate of 91.58%, with an average processing speed of 14.52 FPS. The success rate was 87.50% with an average time of 18.99 seconds for rescuing victims without dummies, and 70.83% with an average time of 46.78 seconds for rescuing victims among dummies. For victim placement, success rates and average times were as follows: 86.67% and 15.29 seconds for the gray safe zone, 93.33% and 15.23 seconds for the yellow safe zone, and 100% with 14.29 seconds for the marker safe zone. Given the high accuracy and speed, this algorithm is effective for scoring points in the Indonesian Search And Rescue Robot competition.
Co-Authors Adi Saputra, Angga Juliat Angga Rusdinar Castrena Abadi, Sarosa Naufalfalah, Tamim Rahayu, Eko Syamsul Rizal