Jun-Wei Chang

Universidad Nacional de Asunción, National Central University

Papers

Total Citations

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About

Jun-Wei Chang is a robotics researcher whose work focuses on enabling mobile robots to perceive and interact with their environments in real time. His key research areas include terrain recognition, autonomous navigation, and human-robot interaction. Chang’s most notable contributions involve developing practical, vision-based methods that allow robots to operate in dynamic, unstructured settings. In his 2016 study on real-time terrain recognition, he proposed a fast estimation method using an RGB-D sensor (XtionPro) mounted on a mobile robot, enabling it to assess uneven terrain for safer movement—a critical step toward robust outdoor robotics. This work has garnered 8 citations. Earlier, in 2012, Chang implemented a people-following mobile robot using omni-wheels and image processing, integrating a notebook with microprocessors (BS2p and PIC16F84A) to achieve reliable tracking. This foundational project, also with 8 citations, demonstrates his ability to combine hardware and software for practical applications. While his citation counts are modest, Chang’s work is valued for its hands-on, implementable solutions that bridge perception and action in mobile robotics, making him a contributor to the development of more autonomous, context-aware machines.