Papers
8
Total Citations
133
H-Index
6
About
Ming Hsiao is a leading robotics researcher whose work spans the critical intersection of simultaneous localization and mapping (SLAM), autonomous navigation, and mobile robot design. His most influential contribution is the development of the Virtual Occupancy Grid Map (VOG-map), a globally deformable mapping approach that enables pose graph SLAM systems to correct accumulated drift through loop closures while preserving free space information for path planning—a foundational advance cited 46 times. Hsiao has also made significant strides in multi-robot SLAM with his MR-iSAM2 algorithm, which introduces a novel multi-root Bayes tree data structure for efficient distributed inference. In the domain of service robotics, he designed an erect wheel-legged stair climbing robot capable of dynamic, self-balancing ascent and descent, integrating multisensor systems using Kinect and IMU for real-time stair recognition. His work on distributed client-server optimization for SLAM addresses the critical challenge of running full SLAM algorithms on resource-constrained devices. With over 130 total citations across his publications, Hsiao’s research continues to shape the future of autonomous navigation in complex, real-world environments.
Research Focus
Key Achievements
Top Papers
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- 2Erect wheel-legged stair climbing robot for indoor service applications27 citations · 2013
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