Baolei Wang

Papers

Total Citations

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About

Baolei Wang is a robotics researcher whose work centers on intelligent control systems and autonomous navigation for mobile robots, with a particular focus on improving trajectory tracking precision in complex, real-world environments. His most cited paper, "High-Precision Trajectory Tracking System for Fork-Shaped Mobile Robot Based on Cascade S_MPC Control" (2024), addresses a critical challenge in robotics: the degradation of tracking accuracy caused by variable loads, changing road friction coefficients, and motor output inconsistencies. Wang’s major contribution lies in developing a cascade structured model predictive control (S_MPC) framework that dynamically regulates wheel speed and turning angle, effectively compensating for these disturbances. This work has garnered attention for its practical relevance to industrial and warehouse automation, where fork-shaped robots must operate reliably under unpredictable conditions. Though early in its citation impact, the paper represents a significant step toward robust, high-precision mobile manipulation. Wang’s research bridges theoretical control design and applied robotics, offering solutions that enhance the safety and efficiency of autonomous material handling. His achievements highlight a commitment to advancing robot autonomy in challenging, real-world settings.