Nagina Nagrani

University of Toronto

Papers

1

Total Citations

17

H-Index

1

About

Dr. Nagina Nagrani’s research lies at the intersection of evolutionary robotics, autonomous systems, and multiagent coordination, with a particular focus on scalable control architectures for complex, real-world tasks. Her most cited work, “Evolving multirobot excavation controllers and choice of platforms using an artificial neural tissue paradigm” (2009, 17 citations), introduces a groundbreaking approach to developing controllers that eliminate the need for human-defined scripts or extensive modeling. By leveraging an artificial neural tissue paradigm, Nagrani demonstrates how controllers can autonomously adapt to multirobot excavation scenarios, enabling flexible platform selection and scalable coordination without requiring a single, pre-specified vehicle. This contribution addresses a critical bottleneck in autonomous excavation—the rigidity of single-robot systems—and opens pathways for more robust, decentralized robotic teams. Though her citation count reflects a focused, early-career impact, the novelty of her methodology has influenced subsequent work in evolutionary robotics and swarm intelligence. Nagrani’s research exemplifies how bio-inspired computation can solve practical engineering challenges, offering a blueprint for developing adaptive, multirobot systems in unstructured environments. Her work remains a valuable reference for researchers exploring neural tissue-based control in autonomous construction and planetary exploration.

Research Focus

Key Achievements

1
H-Index
1
Papers
17
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Evolving multirobot excavation controllers and choice of platforms using an artificial neural tissue paradigm
17 citations · 2009
📈 Most Prolific Year: 2009 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Toronto

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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