Yuehang Ma
Papers
2
Total Citations
10
H-Index
2
About
Yuehang Ma is a robotics researcher specializing in autonomous systems, with a primary focus on self-localization techniques for mobile robots operating in dynamic environments. His work centers on enabling robots to determine their position in real-time without external infrastructure—a critical capability for autonomous navigation and cooperative multi-robot tasks. Ma’s most cited paper, “Real-time Self-localization using Model-based Matching for Autonomous Robot of RoboCup MSL” (2020, 8 citations), introduces a method that leverages an omni-directional camera to match observed features with a known model, allowing a soccer robot to localize itself rapidly during gameplay. This contribution directly supports the RoboCup Middle-Size League’s goal of fully autonomous soccer. Building on this, his 2022 paper “A Self-Localization Method Using a Genetic Algorithm Considered Kidnapped Problem” (2 citations) addresses the “kidnapped robot problem,” where a robot is moved to an unknown location without warning—a challenging test of robustness. By applying a genetic algorithm, Ma’s approach enables recovery from such disruptions, enhancing reliability in real-world scenarios. His work is foundational for researchers in field robotics, autonomous navigation, and RoboCup, demonstrating practical solutions for localization under uncertainty.
Research Focus
Key Achievements
Top Papers
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- 2