Muhammad Akbaryan Anandito
Papers
1
Total Citations
17
H-Index
1
About
Muhammad Akbaryan Anandito is a robotics researcher whose work centers on autonomous navigation and mapping for mobile robots in unknown environments. His most influential contribution, the 2019 study "Research Study of Occupancy Grid Map Mapping Method on Hector SLAM Technique," has garnered 17 citations and addresses a fundamental challenge in robotics: enabling differential drive mobile robots to perceive and represent unfamiliar indoor spaces. By integrating the occupancy grid map method with Hector SLAM, Anandito developed a robust approach that allows robots to construct accurate environmental representations in real time, even without odometry data. This work is particularly significant for applications in search-and-rescue, warehouse automation, and domestic service robots, where reliable mapping in GPS-denied environments is critical. Anandito’s research bridges theoretical SLAM algorithms with practical implementation on resource-constrained platforms, offering a scalable solution for autonomous navigation. His findings have informed subsequent studies in low-cost robotics and sensor fusion, establishing him as a contributor to the advancement of simultaneous localization and mapping in indoor settings.
Research Focus
Key Achievements
Top Papers
- 1Research Study of Occupancy Grid map Mapping Method on Hector SLAM Technique17 citations · 2019