Natalia Ogorelysheva
Papers
4
Total Citations
10
H-Index
2
About
Natalia Ogorelysheva is a leading researcher in multi-robot systems, with a focus on making autonomous fleets resilient in real-world industrial and emergency settings. Her work centers on automated guided vehicles (AGVs) and cross-domain orchestration, addressing critical gaps in how robot teams handle faults, failures, and emergencies without human intervention. Her most cited paper (2023, 4 citations) tackles the high-stakes problem of mitigating emergency stop collisions in AGV fleets during control failures—a vital safety contribution for dynamic logistics and production environments. She further advances the field with her HERO framework (2024, 2 citations), a cross-domain human-enhanced robot orchestration system that enables seamless multi-robot emergency handling across disaster management and logistics, overcoming challenges like unstable networks and large operational areas. Ogorelysheva also contributes foundational resources, such as the CROSSStacks dataset (2023, 1 citation), which simulates storage allocation strategies for cross-docking block-stacking warehouses. Her work is notable for bridging theoretical autonomy with practical troubleshooting, as seen in her 2023 paper on autonomous fault management. With a growing citation footprint, Ogorelysheva is shaping the future of robust, self-healing multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2On Troubleshooting in AGV-based Autonomous Systems3 citations · 2023
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- 4