Jakkree Srinonchat

Rajamangala University of Technology

Papers

9

Total Citations

95

H-Index

4

About

Jakkree Srinonchat is a robotics and artificial intelligence researcher whose work centers on tactile sensing, object recognition, and humanoid robot systems. He is best known for pioneering the development of piezoresistive tactile sensor arrays designed specifically for humanoid robot hands, combining custom PCB-based hardware with deep learning architectures such as convolutional neural networks (DCNN/CNN) to enable touch-based object recognition. His 2021 paper on tactile object recognition for humanoid robots has garnered 43 citations, establishing him as a significant contributor to the field of robotic perception. Srinonchat has progressively expanded this research through glove-based tactile sensors, multi-input sensor fusion, and hardness recognition using time-series-to-image encoding, demonstrating a consistent drive to replicate human tactile intelligence in robotic systems. His earlier work includes image-processing techniques for stair-climbing robots (2008) and speech emotion recognition using FFT spectrum analysis, reflecting a broad expertise spanning computer vision, signal processing, and robot control. With a cumulative citation record spanning nearly two decades, Srinonchat's research offers meaningful contributions to the advancement of human-like robotic sensing and autonomous manipulation technologies.

Research Focus

Key Achievements

4
H-Index
9
Papers
95
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Tactile Object Recognition for Humanoid Robots Using New Designed Piezoresistive Tactile Sensor and DCNN
43 citations · 2021
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Rajamangala University of Technology

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago