Haoran Guang
Papers
1
Total Citations
1
H-Index
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About
Haoran Guang is a researcher in robotics and control systems, with a primary focus on safe autonomous navigation for mobile robots in complex environments. His key research areas include nonlinear model predictive control (NMPC), obstacle avoidance, and safety-critical path planning for car-like robots operating under sensing constraints. Guang’s major contribution lies in developing a safety-critical NMPC framework that enables robots with limited detection ranges to track targets while navigating obstacle-laden scenes. By introducing a temporary artificial reference point within the robot’s detection region, his work addresses the challenge of maintaining safe trajectories when the true target is outside the sensor’s field of view—a practical limitation in real-world deployments. His 2025 paper, “Safety Critical NMPC in Obstacle-Existing Scenes for Car-Like Mobile Robots With Limited Detection,” has garnered initial citations, signaling growing interest in his approach. This work is notable for bridging theoretical control design with realistic sensor constraints, offering a scalable solution for applications in warehouse logistics, autonomous driving, and field robotics. Guang’s research stands out for its pragmatic focus on safety guarantees under imperfect sensing, making it highly relevant for engineers and researchers advancing robust autonomous systems.
Research Focus
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Top Papers
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