Damoon Soudbakhsh
Papers
2
Total Citations
10
H-Index
2
About
Damoon Soudbakhsh is a researcher whose work lies at the intersection of robotics, control theory, and autonomous systems, with a particular focus on motion planning for multi-vehicle and non-Euclidean environments. His major contributions include developing probabilistic and optimal trajectory planning methods that address the challenges of coordinating multiple non-holonomic vehicles in constrained, crowded spaces—such as gridlocked intersections or tight parking areas—where decoupled planning approaches often fail. His 2023 paper, "Probabilistic motion planning for non-Euclidean and multi-vehicle problems," has garnered 7 citations, reflecting its growing influence in the field. In his 2021 work, "Optimal Localized Trajectory Planning of Multiple Non-holonomic Vehicles," he introduced a joint planning framework that ensures feasible, collision-free navigation for multiple agents in complex scenarios. Soudbakhsh’s research is notable for its practical relevance to autonomous driving and swarm robotics, offering scalable solutions that bridge theoretical rigor with real-world constraints. His work continues to shape how researchers approach decentralized coordination in dynamic environments, making him a rising voice in autonomous systems and multi-agent planning.
Research Focus
Key Achievements
Top Papers
- 1
- 2Optimal Localized Trajectory Planning of Multiple Non-holonomic Vehicles3 citations · 2021