Papers
3
Total Citations
24
H-Index
2
About
Ming Ma is a robotics researcher specializing in intelligent control systems, flexible manipulator dynamics, and bionic locomotion. Their most significant contribution is the development of an open-closed-loop iterative learning control method for multiple flexible manipulator robot systems, which achieves consensus tracking of desired trajectories while mitigating the effects of system flexibility—a critical challenge in precision robotics. This work, published in 2019, has garnered 19 citations and represents a foundational approach for controlling complex, repeatable motion tasks in multi-manipulator setups. Ma has also advanced the field of bio-inspired robotics through the design and performance analysis of a bionic quadruped robot with an articulated spine, exploring how spinal mechanisms enhance locomotion efficiency and stability. Additionally, their research on intelligent obstacle avoidance for mobile robots in multi-barrier environments, which employs a minimum risk index for path segmentation, addresses practical challenges in autonomous navigation. With a portfolio spanning from theoretical control strategies to applied mechanical design, Ming Ma’s work is shaping the next generation of adaptive, flexible robotic systems for both industrial and exploratory applications.
Research Focus
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Top Papers
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