Hossein Moradi Pari

Sharif University of Technology

Papers

1

Total Citations

3

H-Index

1

About

Hossein Moradi Pari’s research centers on multi-robot systems, autonomous navigation, and dynamic path planning, with a particular focus on enabling robotic teams to intelligently track moving targets. His most cited work, “Model predictive based dynamic path planning for single target tracking and formation” (2013), introduces a novel algorithm that allows a fleet of vehicle-modeled robots to autonomously decide between tracking an unknown-trajectory object or searching the mission region for future targets. This contribution addresses a critical challenge in cooperative robotics: balancing real-time pursuit with exploratory search under uncertainty. While his citation count of 3 reflects a niche but foundational impact, the work demonstrates his expertise in model predictive control and formation strategies—key tools for applications in surveillance, search-and-rescue, and autonomous logistics. Moradi Pari’s research offers practical frameworks for deploying adaptive, decision-making robot swarms, making his contributions valuable for students and engineers advancing intelligent autonomous systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Model predictive based dynamic path planning for single target tracking and formation
3 citations · 2013
📈 Most Prolific Year: 2013 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Sharif University of Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago