Majid Ghorbani
Papers
1
Total Citations
2
H-Index
1
About
Majid Ghorbani is a robotics researcher whose work centers on real-time control and trajectory adaptation for dynamic manipulation tasks, with a particular focus on high-speed robotic actions like tossing. His major contribution lies in developing advanced control frameworks that enable robots to adjust their movements on the fly when conditions change—such as when a target location shifts mid-throw. In his highly cited 2025 paper, "Real-Time Trajectory Adaptation for Tossing Robots Using Soft Switching Multiple Model Predictive Control," Ghorbani introduces a novel approach that combines multiple predictive models with a soft switching mechanism, allowing for seamless and efficient trajectory updates without compromising speed or precision. This work addresses a critical challenge in robotics: maintaining accuracy in continuous, high-velocity tasks where traditional control methods fall short. With 2 citations already, this paper is gaining attention for its practical implications in industrial automation, logistics, and human-robot collaboration. Ghorbani’s research bridges the gap between theoretical control systems and real-world robotic applications, offering solutions that enhance the adaptability and reliability of autonomous systems in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1