Sutono Effendi

Engineering Systems (United States), Monash University

Papers

Total Citations

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About

Sutono Effendi’s research lies at the intersection of robotics, computer vision, and assistive technology, with a focus on developing intelligent systems that enhance independence for elderly and disabled individuals. His most cited work, “Robot manipulation grasping of recognized objects for assistive technology support using stereo vision” (2008, 10 citations), introduces a novel approach to robotic grasping by combining a 2.5D disparity map with a Scale Invariant Feature Transform (SIFT) algorithm. This method significantly reduces matching time through stereo segmentation, enabling more accurate object recognition and manipulation—a critical step toward practical assistive robots. In his follow-up paper, “An intelligent robotic assistive living system” (2009, 3 citations), Effendi expands this vision by designing a complete robotic system capable of performing everyday tasks autonomously within home or care settings. Though his citation counts are modest, Effendi’s work is notable for its early integration of vision-based grasping with real-world assistive applications, laying groundwork for more sophisticated human-robot interaction systems. His contributions highlight the potential of robotics to improve quality of life by reducing dependence on human caregivers for routine tasks.