Mohammad Rusli
Papers
1
Total Citations
3
H-Index
1
About
Mohammad Rusli is a robotics researcher whose work focuses on intelligent navigation and control systems for autonomous mobile robots. His key research areas include model predictive control, collision avoidance, and autonomous path planning. In his most cited work, "Collision Avoidance System with Model Predictive Control for Mobile Robot Navigation" (2022), Rusli addresses a fundamental challenge in robotics: enabling mobile robots to safely navigate dynamic environments while executing mission-critical tasks. The paper proposes a control framework that not only moves the robot's actuators—whether wheels or legs—but also interprets real-time environmental data to prevent collisions. With 3 citations, this contribution is gaining traction among researchers working on safe autonomous navigation. Rusli’s work bridges the gap between theoretical control algorithms and practical robotic deployment, offering solutions that are essential for applications ranging from warehouse logistics to search-and-rescue operations. His research is particularly valuable for students and engineers seeking robust, real-time navigation strategies that balance mission efficiency with safety.
Research Focus
Key Achievements
Top Papers
- 1