Andy Suryowinoto

Papers

Total Citations

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About

Andy Suryowinoto is a robotics and automation researcher whose work bridges intelligent systems and maritime technology. His most cited paper, "The prototype of A Forklift Robot Based on AGV System and Android Wireless Controlled for Stacked Shelves" (2020, 7 citations), introduces a novel automated guided vehicle (AGV) forklift prototype that integrates Android-based remote monitoring for precise material handling in warehouse environments. This contribution advances industrial automation by enabling cost-effective, wireless-controlled logistics solutions. More recently, Suryowinoto has ventured into underwater robotics with "Estimation of remote operated vehicle motion in XY plane using unscented Kalman filter" (2023, 2 citations), addressing Indonesia's underexplored underwater territories. By applying unscented Kalman filtering to remotely operated vehicles (ROVs), his work enhances motion estimation accuracy in XY planes, a critical step toward safer and more efficient deep-sea exploration. Suryowinoto’s research demonstrates a clear trajectory from terrestrial automation to marine robotics, reflecting a commitment to solving real-world challenges in logistics and maritime technology. His interdisciplinary approach—combining control systems, wireless communication, and state estimation—positions him as an emerging innovator in both industrial and underwater robotics.