Hendri Himawan Triharminto
Papers
4
Total Citations
46
H-Index
3
About
Hendri Himawan Triharminto is a robotics researcher whose work centers on intelligent path planning for mobile robots, with a particular focus on overcoming fundamental limitations in the Artificial Potential Field (APF) method. His major contributions address two critical challenges in autonomous navigation: the GNRON (Goal Nonreachable with Obstacles Nearby) problem and the local minima issue that often traps robots in suboptimal positions. By developing novel repulsive potential functions, Triharminto has enabled robots to successfully navigate toward their goals even when obstacles are clustered nearby—a scenario that traditionally caused failure. His most cited paper, "An Integrated Artificial Potential Field Path Planning with Kinematic Control for Nonholonomic Mobile Robot" (24 citations), advances the field by moving beyond the common point-mass robot assumption, integrating kinematic constraints directly into the planning process for more realistic, implementable solutions. Further work on framework transformation for local information addresses the practical challenge of real-time navigation in vast environments where global sensor data is unavailable. Triharminto’s research bridges the gap between theoretical path planning and real-world robotic deployment, making his work essential reading for engineers and researchers developing autonomous ground vehicles.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4