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About

Hari Maghfiroh is a robotics researcher advancing the frontiers of autonomous navigation, control systems, and artificial intelligence for mobile robots. His work spans three interconnected domains: intelligent object detection, self-balancing robot control, and simultaneous localization and mapping (SLAM). Maghfiroh's most impactful contribution is the development of a ball detection system for wheeled soccer robots using the MobileNetV2 SSD method, demonstrating how lightweight deep learning models can enable real-time object recognition in dynamic environments. He has also made significant strides in two-wheeled self-balancing robot navigation, creating virtual map and sensor approaches that allow these highly maneuverable platforms to operate autonomously without physical sensors. His research on differential drive mobile robots integrates PID control with Hector SLAM for precise mapping and localization, with direct applications in transportation and logistics. Beyond robotics, Maghfiroh has applied IoT and automation to aquaculture, developing an automatic feeder with remote monitoring for catfish biofloc systems. With over 16 citations across his most-cited works, his research bridges theoretical control systems with practical implementations, offering valuable insights for students and researchers working on autonomous robot navigation, embedded AI, and mechatronic system design.