Camilo Perez

University of Alberta, Universidad de Los Andes

Papers

9

Total Citations

81

H-Index

4

About

Camilo Perez is a robotics and computer vision researcher whose work sits at the intersection of visual perception, human-robot interaction, and robotic manipulation. His research spans incremental machine learning for robot scene understanding, visual tracking, teleoperation, and visual servoing — areas where he has made meaningful contributions to bridging the gap between laboratory performance and real-world robotic deployment. Perez's most influential work focuses on enabling robots to learn continuously through human-robot interaction, leveraging Convolutional Neural Networks for adaptive visual scene understanding — a contribution that has garnered 34 citations and reflects growing community interest in practical, deployable robot perception. His 2013 work on registration-based visual tracking using approximate nearest neighbour search (17 citations) introduced a robust algorithm capable of handling larger per-frame motions than conventional methods, advancing real-time tracking reliability. Beyond perception, Perez has explored teleoperation interfaces, demonstrating how smartphone-based controls and predictive displays can make remote robot manipulation more accessible and delay-resilient. His work on transferring human grasping knowledge to robots and 4-DoF object tracking for fine manipulation further illustrates a consistent drive toward practical, human-centered robotics. With contributions spanning nearly a decade, Perez represents a researcher dedicated to making robots more perceptive, adaptable, and collaborative partners in real-world environments.

Research Focus

Key Achievements

4
H-Index
9
Papers
81
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Incremental learning for robot perception through HRI
34 citations · 2017
📈 Most Prolific Year: 2017 (5 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: University of Alberta, Universidad de Los Andes

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago