Junqiao Ma
Papers
1
Total Citations
6
H-Index
1
About
Junqiao Ma is a researcher advancing the field of intelligent robotic assembly through the integration of deep reinforcement learning and multimodal perception. Their primary research areas include robotic manipulation, sensor fusion, and automated manufacturing, with a focus on solving complex assembly tasks such as peg-in-hole operations. Ma’s most notable contribution is the development of a combined perception alignment method that synergizes tactile and visual feedback, addressing the limitations of each modality: tactile sensing excels at capturing contact forces but lacks spatial sensitivity, while vision provides precise positional awareness but struggles with contact state detection. This work, published in 2021 and cited 6 times, demonstrates a practical framework for improving assembly precision and adaptability in industrial settings. By bridging perception gaps, Ma’s research offers a pathway toward more robust, autonomous robotic systems capable of handling high-tolerance tasks. Their work holds promise for advancing smart manufacturing and human-robot collaboration, making it a valuable reference for students and engineers exploring reinforcement learning applications in robotics.
Research Focus
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Top Papers
- 1