Samiadji Herdjunanto
Papers
1
Total Citations
3
H-Index
1
About
Samiadji Herdjunanto is a researcher specializing in mobile robot path planning, with a particular focus on overcoming the limitations of the artificial potential field (APF) approach in constrained environments. His key research areas include autonomous navigation, omnidirectional sensing, and obstacle avoidance for mobile robots operating in corridor-like settings. Herdjunanto’s most notable contribution is his work on integrating omnidirectional sensing to address the local minimum problem in APF-based path planning, a common issue that traps robots in dead-end configurations. His 2018 paper on this topic, which has garnered 3 citations, proposes a novel method to escape local minima by leveraging 360-degree environmental perception, enabling smoother and more reliable navigation in corridors. This work is significant for its practical application in real-world indoor robotics, where traditional APF methods often fail. Herdjunanto’s research has been recognized for its computational simplicity and effectiveness, offering a valuable solution for autonomous systems in tight spaces. His contributions continue to influence the development of more robust and efficient path planning algorithms for mobile robots.
Research Focus
Key Achievements
Top Papers
- 1