Navid Pirmarzdashti
Papers
3
Total Citations
32
H-Index
2
About
Navid Pirmarzdashti is a robotics researcher focused on achieving long-term autonomy for ground robots operating in unstructured, dynamic environments—particularly in agriculture. His work addresses the critical challenge of enabling robots to navigate safely and efficiently in settings where moving humans, livestock, and other agents are present. Pirmarzdashti’s major contributions include developing resource- and response-aware path planning frameworks that allow robots to operate continuously over extended periods, even under on-board constraints like limited energy. His most cited paper, "Resource and Response Aware Path Planning for Long-Term Autonomy of Ground Robots in Agriculture" (2022), has garnered 26 citations and introduces a novel approach for navigating farms while accounting for dynamic obstacles. He has also advanced path planning in crowded spaces by integrating generative recurrent neural networks with Monte Carlo Tree Search, moving beyond hand-crafted motion models. Additionally, his hierarchical framework for robust, long-term deployment in large-scale farming addresses the practical demands of real-world agricultural robotics. Pirmarzdashti’s work is shaping the future of autonomous systems in complex, human-inhabited environments.
Research Focus
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Top Papers
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