Papers
8
Total Citations
97
H-Index
4
About
Yizhe Chang is a robotics researcher whose work spans autonomous navigation, human-robot interaction, and educational technology. His most influential contributions center on two major themes: intelligent robotic wheelchairs and multi-robot path planning. Chang's pioneering work on egocentric vision-based robotic wheelchairs—among his most cited research, with 26 and 37 citations respectively—has meaningfully advanced assistive technology for elderly and disabled individuals, enabling hands-free mobility through computer vision systems that eliminate the need for manual joystick control. His 2018 paper on optimal multi-robot coverage path planning, his most cited work, introduced an improved ant colony optimization algorithm to construct ideal-shaped spanning trees, offering a robust solution to a challenging problem in autonomous robotics. Chang has also made significant contributions to shared autonomy, developing systems that intelligently balance user preferences with robotic decision-making to improve wheelchair safety and usability. More recently, his research has expanded into educational innovation, exploring Internet of Things technologies to enable remote collaboration in robotics courses—a timely contribution in the era of distance learning. Collectively, his work reflects a researcher deeply committed to making robotics both more capable and more accessible.
Research Focus
Key Achievements
Top Papers
- 1Optimal Multirobot Coverage Path Planning: Ideal-Shaped Spanning Tree37 citations · 2018
- 2Usability Studies of an Egocentric Vision-Based Robotic Wheelchair26 citations · 2020
- 3Egocentric Computer Vision for Hands-Free Robotic Wheelchair Navigation12 citations · 2023
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- 7Application of Internet of Things in Online Robotics Class2 citations · 2024
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