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About

Hendriyawan Achmad is a robotics and computer vision researcher whose work centers on autonomous mobile systems, human-robot interaction, and environmental mapping. His research has made meaningful contributions to the development of intelligent robotic systems capable of navigating and interpreting complex real-world environments. Most notably, his 2016 study on 3D scene reconstruction using stereo vision — his most cited work with 12 citations — demonstrated how camera calibration and disparity mapping can be combined to generate accurate spatial coordinates, advancing practical approaches to robot perception. Achmad has also been a consistent advocate for Robot Operating System (ROS) as a foundational platform for robotics research, applying it across multiple projects including teleoperated indoor exploration, industrial plant mapping, and Ackerman-model mobile robot navigation in unknown environments. His human-robot interaction research highlights the practical challenges researchers face in real-world experimental settings while proposing robust methods for remote collaboration between humans and mobile robots. Collectively, his body of work — accumulating over 20 citations — reflects a focused commitment to bridging theoretical robotics frameworks with deployable, real-world autonomous systems relevant to both industrial inspection and exploratory robotics applications.