I.-Ming Chen

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About

I.-Ming Chen is a robotics researcher whose work spans industrial automation, autonomous navigation, and construction quality assessment. His major contributions include developing robust robotic systems for real-world challenges, most notably a robot designed for item picking in the Amazon Robotics Challenge, which integrated grasping, vision, and motion planning to achieve reliable performance. This work, cited 30 times, demonstrates his focus on practical, deployable solutions. Chen also advanced autonomous maritime navigation by leveraging historical AIS data to generate efficient route plans for surface vessels, a method cited 16 times that highlights his innovative use of existing datasets. Additionally, he pioneered the QuicaBot, a novel autonomous robot for post-construction quality assessment that detects hollowness, cracks, and alignment issues—a first-of-its-kind system cited 6 times. Chen’s research is characterized by its direct applicability to industry, bridging the gap between theoretical robotics and tangible, high-impact applications. His work on the Amazon Robotics Challenge and QuicaBot underscores his ability to tackle complex, multidisciplinary problems, making him a notable figure in applied robotics and automation.