Papers

7

Total Citations

61

H-Index

4

About

Felipe G. Oliveira is a robotics researcher whose work centers on autonomous navigation, terrain perception, and visual enhancement for field and underwater robots. His most influential contribution, "Speed-invariant terrain roughness classification and control based on inertial sensors" (23 citations), pioneered the use of inertial data to assess traversability in real time—a critical capability for autonomous vehicles operating in agriculture, mining, and environmental monitoring. Building on this, Oliveira developed augmented navigation cost maps that integrate deep learning and inertial sensing to improve path planning over rough terrain. His research extends to underwater robotics, where he proposed a fusion-based image enhancement technique to improve visual data quality for search-and-rescue and marine monitoring missions. More recently, he has explored low-light image enhancement using Bayesian optimization and discrete movement control for bio-inspired multi-legged robots. Across his publications, Oliveira consistently addresses the challenge of enabling robots to perceive and adapt to complex, unstructured environments. With over 60 total citations and a growing portfolio spanning terrain classification, 3D mapping, and image restoration, his work is shaping safer, more reliable autonomous systems for demanding real-world applications.

Research Focus

Key Achievements

4
H-Index
7
Papers
61
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Speed-invariant terrain roughness classification and control based on inertial sensors
23 citations · 2017
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Universidade Federal de Minas Gerais, Universidade Federal do Amazonas

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago