Meng Dechao

Papers

Total Citations

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About

Meng Dechao is a researcher in autonomous robotics and computer vision, with a focus on bio-inspired navigation and obstacle avoidance. His work centers on leveraging optical flow—the pattern of apparent motion in visual scenes—to enable robots to navigate complex environments without relying on expensive sensors. His most cited paper, "An experimental evaluation of balance strategy based obstacle avoidance" (2016, 5 citations), systematically tests optical flow-based methods in both synthetic and real-world settings, demonstrating how a balance strategy can help robots avoid obstacles efficiently and robustly. This contribution is particularly valuable for developing low-cost, vision-driven autonomous systems, such as drones and ground vehicles. While his citation count is modest, his research addresses a fundamental challenge in robotics: achieving reliable, real-time navigation with minimal computational resources. Meng’s work bridges theoretical insights from insect vision and practical engineering, offering a foundation for future studies in lightweight, biologically inspired control systems. His evaluations provide a benchmark for comparing optical flow strategies, making his research a useful reference for students and engineers exploring vision-based autonomy.