Oliver Limoyo

University of Toronto

Papers

7

Total Citations

49

H-Index

5

About

Oliver Limoyo is a roboticist whose research spans autonomous navigation, manipulation, and human-robot interaction, with a focus on enabling robots to operate intelligently in unstructured, contact-rich environments. His most cited work, "The Canadian Planetary Emulation Terrain Energy-Aware Rover Navigation Dataset" (14 citations), provides a critical resource for developing energy-efficient path planning for solar-powered planetary rovers, directly supporting future Moon and Mars missions. Limoyo has made significant contributions to imitation learning, as demonstrated in his 2024 paper on multimodal, force-matched learning using a see-through visuotactile sensor (9 citations), which allows robots to master tasks involving slipping and sliding—a longstanding challenge in manipulation. He also advanced inverse kinematics with his "Generative Graphical Inverse Kinematics" (9 citations), offering a novel approach to quickly and reliably find multiple solutions for complex robot arms. Notably, his work on the "ANSEL Photobot" (7 citations) showcases semantic intelligence by integrating large language models for robotic planning, enabling a robot to act as an autonomous event photographer with contextual awareness. With over 50 total citations, Limoyo’s research is shaping the future of robust, energy-aware, and semantically intelligent robotic systems.

Research Focus

Key Achievements

5
H-Index
7
Papers
49
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
The Canadian Planetary Emulation Terrain Energy-Aware Rover Navigation Dataset
14 citations · 2020
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: University of Toronto

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago