Daniel Grosu
Papers
1
Total Citations
9
H-Index
1
About
Daniel Grosu is a leading researcher in autonomous systems and sustainable robotics, with a focus on optimizing the coordination and lifecycle management of multi-robot fleets. His most-cited work, "A Maintenance-Aware Approach for Sustainable Autonomous Mobile Robot Fleet Management" (2023), introduces a groundbreaking framework that integrates task allocation with predictive maintenance scheduling. By enabling autonomous mobile robots (AMRs) to operate continuously for 24/7 while minimizing downtime, Grosu’s approach significantly enhances throughput and operational efficiency in industrial and logistics settings. This contribution addresses a critical gap in robotics research—balancing long-term sustainability with real-time performance demands. With 9 citations in its first year, the paper has already influenced both academic discourse and practical deployment strategies. Grosu’s work is particularly notable for bridging theoretical optimization models with real-world constraints, such as battery degradation and wear-and-tear, ensuring that fleets remain productive over extended periods. His research is essential reading for engineers and scientists working on scalable, resilient autonomous systems, offering a blueprint for the next generation of intelligent, self-sustaining robotic operations.
Research Focus
Key Achievements
Top Papers
- 1