Papers
2
Total Citations
28
H-Index
1
About
Qihua Ma is a researcher specializing in mobile robotics and autonomous vehicle motion planning, with a focus on developing advanced optimization algorithms for dynamic environments. Their major contributions lie in enhancing meta-heuristic approaches for path planning, particularly through the integration of artificial potential fields with multi-objective optimization techniques. Ma's most cited work, "Dynamic path planning for mobile robots based on artificial potential field enhanced improved multiobjective snake optimization (APF‐IMOSO)" (2024), has garnered 27 citations, demonstrating its impact on improving robot navigation efficiency and safety. This work introduces a novel hybrid algorithm that combines the strengths of artificial potential fields with snake optimization to address complex, real-time path planning challenges. More recently, Ma has extended these methods to autonomous vehicle motion planning with "MESO: a multi-strategy enhanced snake optimizer" (2025), showcasing ongoing innovation in the field. Their research is notable for its practical applications in robotics and autonomous systems, offering scalable solutions for obstacle avoidance and trajectory optimization. Ma's work is essential reading for students and researchers interested in computational intelligence, robotics, and autonomous navigation.
Research Focus
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Top Papers
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