Riyanto Riyanto
Bandung Institute of Technology, Informatics Institute of Technology
Papers
8
Total Citations
124
H-Index
6
About
Riyanto Riyanto is a prominent robotics researcher whose work centers on humanoid robot systems, human-robot interaction, and intelligent control algorithms. His research has made significant contributions to advancing autonomous robotic behavior, particularly in enabling humanoid robots to perceive, communicate, and navigate effectively in real-world environments. Among his most impactful contributions is his work on multimodal human-robot communication, including hand gesture recognition using K-means clustering and Support Vector Machine (41 citations) and the integration of Indonesian speech and gesture recognition for robot control — work that notably addresses accessibility for deaf and elderly users. His path planning research, applying the A-Star search algorithm to humanoid robot navigation (36 citations), has meaningfully advanced autonomous indoor mobility for home-assistant robots. Riyanto has also made technical strides in robot locomotion stability, developing gait controllers using Kalman filters, PD controllers, and fuzzy logic to maintain balanced bipedal walking across challenging surfaces. His object detection work leveraging SIFT-KNN classification further demonstrates his breadth across computer vision and servo control systems. With over 120 cumulative citations, his research collectively pushes the boundaries of intelligent, socially aware humanoid robotics, making him a valuable voice in both academic and applied robotics communities.
Research Focus
Key Achievements
Top Papers
- 1Hand gesture recognition using K-means clustering and Support Vector Machine41 citations · 2018
- 2Humanoid Robot Path Planning and Rerouting Using A-Star Search Algorithm36 citations · 2019
- 3Gait Controllers on Humanoid Robot Using Kalman Filter and PD Controller15 citations · 2018
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