Papers
7
Total Citations
57
H-Index
5
About
Abolfazl Lavaei is a researcher whose work spans two compelling and increasingly relevant domains: autonomous aerial robotics and formal control of large-scale stochastic systems. His early research focused on trajectory generation and path planning for unmanned aerial vehicles (UAVs), producing influential work on neural network-based optimal trajectory generation for terrain following (2014, 18 citations) and path planning in complex mountainous environments (2016, 10 citations). His 2017 contribution extended these methods to three-dimensional urban delivery scenarios, reflecting the growing real-world demand for intelligent drone navigation. Lavaei subsequently pivoted toward formal methods in control engineering, developing scalable software tools for safety-critical autonomous systems. His AMYTISS tool (2020), which garnered 12 combined citations across publications, introduced parallelized controller synthesis for large-scale discrete-time stochastic systems using finite Markov decision process abstractions — a significant advance for applications such as traffic networks and self-driving vehicles. His more recent IMPaCT framework (2024, 6 citations) continues this trajectory, addressing interval MDP construction at scale. His additional work on space debris orbit determination further demonstrates a versatile research profile bridging aerospace engineering and formal verification, making him a noteworthy contributor across multiple safety-critical domains.
Research Focus
Key Achievements
Top Papers
- 1
- 2Path generation for flying robots in mountainous regions10 citations · 2016
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- 6AMYTISS5 citations · 2020
- 7