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About

Dwi Arman Prasetya is an Indonesian robotics researcher whose work spans intelligent control systems, computer vision, and autonomous robot navigation. His research career reflects a sustained commitment to advancing human-robot interaction and multi-robot coordination, bridging foundational algorithmic methods with practical AI-driven applications. Prasetya's early contributions focused on cooperative control of multiple mobile robots, employing Particle Swarm Optimization (PSO) to enable autonomous target tracking and obstacle avoidance in unknown environments — work that garnered 13 combined citations and laid the groundwork for his later pursuits. He subsequently turned toward deep learning applications in robotics, producing his most-cited work: a real-time face detection system for a 2-DOF robot head using Deep Integral Image Cascade (2020, 16 citations), demonstrating impressive human-like robot responsiveness. Complementing this, his CNN-based spatial deep learning framework for autonomous wheeled robots (9 citations) showcased his aptitude for integrating neural architectures into practical robotic platforms. His research on voice-pattern telemetry control further highlights his interest in intuitive human-machine interfaces. With over 40 cumulative citations, Prasetya represents a productive voice in Indonesian robotics research, consistently pushing toward robots that perceive, decide, and interact more naturally with the world around them.