Mohammad Khosravi
Papers
1
Total Citations
3
H-Index
1
About
Mohammad Khosravi is a researcher whose work centers on multi-robot systems, dynamic path planning, and formation control, with a particular focus on enabling autonomous agents to collaboratively track moving targets in uncertain environments. His most cited paper, "Model predictive based dynamic path planning for single target tracking and formation" (2013), introduces a novel algorithm that allows a team of vehicles to autonomously decide whether to pursue a moving object or search the mission region for future targets, all without prior knowledge of the object's trajectory. This contribution addresses a critical challenge in robotics—balancing real-time tracking with exploratory search—and has laid groundwork for adaptive, model-predictive strategies in swarm robotics. While his citation count is modest, the work demonstrates a forward-thinking approach to decentralized decision-making under uncertainty, a topic of growing importance in autonomous systems. Khosravi’s research is particularly relevant for students and engineers interested in the intersection of control theory, artificial intelligence, and multi-agent coordination, offering practical insights into how robots can intelligently prioritize tasks in dynamic, real-world scenarios.
Research Focus
Key Achievements
Top Papers
- 1