Ramtin Madani

The University of Texas at Arlington

Papers

1

Total Citations

5

H-Index

1

About

Ramtin Madani is a rising researcher in robotics and optimization, with a focus on multi-robot coordination and motion planning. His most-cited work, "Multi-Robot Motion Planning via Parabolic Relaxation" (2022), addresses a fundamental challenge in the field: how to coordinate multiple robots efficiently without sacrificing safety or completeness. Madani introduces a novel parabolic relaxation technique that transforms the notoriously hard multi-robot motion planning (MRMP) problem into a more tractable convex optimization, enabling scalable and provably safe coordination. This work, garnering 5 citations, is notable for offering a rigorous theoretical foundation while maintaining practical applicability—a rare balance in multi-robot systems. Madani’s contributions are particularly impactful for applications in warehouse automation, drone swarms, and autonomous exploration, where decentralized yet reliable planning is critical. By bridging optimization theory and robotics, his research provides a pathway to reduce the computational complexity that has long hindered large-scale multi-robot deployments. As the field moves toward greater autonomy, Madani’s parabolic relaxation approach stands out as a promising tool for enabling real-time, collision-free motion planning in complex environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
5
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Multi-Robot Motion Planning via Parabolic Relaxation
5 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: The University of Texas at Arlington

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago