Chang Ruijuan
Papers
1
Total Citations
5
H-Index
1
About
Chang Ruijuan is a researcher whose work lies at the intersection of computer vision and autonomous robotics, with a particular focus on bio-inspired navigation. Her most cited study, "An experimental evaluation of balance strategy based obstacle avoidance" (2016), provides a rigorous assessment of optical flow methods for robot navigation. By systematically testing the balance strategy—a technique inspired by insect vision—in both synthetic and real-world environments, she has contributed valuable empirical insights into how autonomous systems can avoid obstacles using visual cues alone. This work, which has garnered 5 citations, serves as a practical benchmark for researchers developing vision-based navigation algorithms. Chang’s research is notable for bridging theoretical optical flow models with real-world robotic applications, offering clear guidance on the strengths and limitations of balance-based approaches. Her findings are particularly relevant for students and engineers working on lightweight, vision-driven robots where computational efficiency is critical. Through her careful experimental design and clear reporting, Chang Ruijuan has established herself as a thoughtful contributor to the ongoing effort to make autonomous navigation more reliable and nature-inspired.
Research Focus
Key Achievements
Top Papers
- 1An experimental evaluation of balance strategy based obstacle avoidance5 citations · 2016