Hilwadi Hindersah
Papers
7
Total Citations
51
H-Index
4
About
Hilwadi Hindersah is a robotics researcher whose work spans control systems, humanoid locomotion, multi-agent coordination, and human-robot interaction. His most influential contribution, "Application of reinforcement learning on self-tuning PID controller for soccer robot multi-agent system" (23 citations), pioneered adaptive control for competitive robotics, enabling faster and more precise robot movements through machine learning-based parameter tuning. Hindersah has made significant advances in bipedal robot stability, developing fuzzy logic controllers for standing and walking (10 citations) and center-of-mass-based walking pattern generators with gravity compensation (5 citations). His research on slope balancing using sensor fusion (3 citations) addresses real-world terrain challenges for humanoid robots. More recently, Hindersah has explored deep learning applications, including MobileNetV3-based speaker recognition for voice-guided robot navigation (2024) and YOLOv7-based visual servoing for manipulator arms (2023). His work on distributed multi-robot SLAM with consensus particle filtering (4 citations) contributes to collaborative mapping in unknown environments. With a career spanning from reinforcement learning to modern computer vision, Hindersah demonstrates a consistent focus on making robots more autonomous, stable, and responsive—bridging classical control theory with contemporary AI methods to solve practical robotics challenges.
Research Focus
Key Achievements
Top Papers
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- 4Speaker Recognition Using MobileNetV3 for Voice-Based Robot Navigation4 citations · 2024
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- 7YOLOv7-based Visual Servoing on 2-DOF Manipulator Robot2 citations · 2023