Trihastuti Agustinah
Papers
13
Total Citations
81
H-Index
6
About
Dr. Trihastuti Agustinah is a leading researcher in mobile robotics, specializing in collision avoidance, human-robot interaction, and autonomous navigation. Her major contributions include developing the Modified Headed Social Force Model with Hybrid Velocity Obstacles, which enables robots to safely navigate through groups of pedestrians—a critical advancement during the Covid-19 pandemic. She has also pioneered fuzzy Q-learning techniques to minimize state spaces in reinforcement learning for obstacle avoidance, and designed hybrid velocity obstacle methods for multi-modal moving objects. Her work on disturbance compensation using Computed Torque Control with Nonlinear Disturbance Observers has advanced formation control of mobile robots. With over 77 citations across her top papers, Dr. Agustinah's research has significantly impacted safe and efficient robot navigation in human environments. Notably, her 2021 paper on pedestrian-aware collision avoidance has garnered 16 citations, reflecting its influence in the field. Her recent Safe Dynamic Window Approach further enhances human-robot interaction by integrating threat-level indices for safety and comfort. Dr. Agustinah's work is essential reading for researchers developing socially-aware autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 8Robot Orientation Estimation Based on Single-Frame of Fish-eye Image3 citations · 2020
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- 10Obstacle Avoidance Using Safe Dynamic Window Approach for Mobile Robot2 citations · 2024