John Lewis

University of Lisbon

Papers

3

Total Citations

21

H-Index

3

About

John Lewis is a leading researcher in field robotics, specializing in multi-robot coordination, autonomous exploration, and robust localization for large-scale outdoor environments. His work addresses critical challenges in deploying robot fleets for precision agriculture, search and rescue, and industrial inspection. Lewis’s most cited paper, “Collaborative 3D Scene Reconstruction in Large Outdoor Environments Using a Fleet of Mobile Ground Robots” (2022, 13 citations), introduces a framework for efficient, collaborative mapping that enhances situational awareness over vast areas. He further advanced localization reliability with “GEERS: Georeferenced Enhanced EKF Using Point Cloud Registration and Segmentation” (2024, 5 citations), a method fusing wheel odometry, IMU, and GNSS with point cloud corrections for high-accuracy, consistent-rate positioning. His latest notable work, “Frontier Shepherding: A Bio-inspired Multi-robot Framework for Large-Scale Exploration” (2025, 3 citations), draws inspiration from natural shepherding behaviors to optimize exploration efficiency. With a growing citation impact and a focus on practical, scalable solutions, Lewis is shaping the future of autonomous outdoor robotics, enabling robots to operate reliably and collaboratively in complex, unstructured environments.

Research Focus

Key Achievements

3
H-Index
3
Papers
21
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Collaborative 3D Scene Reconstruction in Large Outdoor Environments Using a Fleet of Mobile Ground Robots
13 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Lisbon

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago