Arif Irwansyah

Bielefeld University, Politeknik Elektronika Negeri Surabaya

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About

Arif Irwansyah is a robotics and computer vision researcher whose work centers on real-time, hardware-accelerated systems for multi-robot coordination and autonomous navigation. His primary contributions lie in developing FPGA-based solutions for computationally intensive vision tasks, enabling efficient multi-robot tracking in dynamic environments. His most cited work, "FPGA-based multi-robot tracking" (2017, 20 citations), demonstrates a practical approach to overcoming the memory and processing bottlenecks of traditional algorithms. He further advanced this area by integrating the Circular Hough Transform with graph clustering for shape-based object detection (2015, 8 citations), addressing the high computational demands of circle detection in vision systems. Irwansyah also applies his expertise to humanoid robotics, as seen in his work on the ERISA robot (2021, 4 citations), where he developed walking trajectory control using a Pixy CMUcam5 for target localization. This project highlights his ability to bridge hardware acceleration and practical robot design, contributing to innovations in robotic contest platforms and culturally expressive automation. With a focused publication record, Irwansyah’s research continues to impact the fields of reconfigurable computing, multi-agent systems, and embedded vision.