Nicolas Dalmedico
Universidade Tecnológica Federal do Paraná, Advanced Systems Laboratory
Papers
6
Total Citations
40
H-Index
3
About
Nicolas Dalmedico is a robotics researcher specializing in climbing robots, intelligent perception systems, and GPU-accelerated computing for autonomous navigation. His work focuses on developing advanced control and sensing solutions for robots operating in challenging environments, particularly in industrial inspection applications. Dalmedico’s most cited paper, “Model Predictive Torque Control for Velocity Tracking of a Four-Wheeled Climbing Robot” (2020, 17 citations), addresses the complex dynamics of climbing robots with secure surface coupling, proposing a control strategy to manage nonlinear, time-varying parameters that affect mobility and wheel friction. He has also made significant contributions to high-temperature weld bead inspection with a climbing robot (2024, 9 citations), demonstrating practical industrial impact. His research extends to intelligent 3D perception systems (2019, 7 citations) that use computer vision and machine learning for semantic environment description and dynamic interaction, as well as embedded GPU processing (2017, 3 citations) to enhance real-time point cloud fusion. Dalmedico’s work on sliding window mapping for omnidirectional RGB-D sensors (2019, 2 citations) further showcases his innovation in sensor fusion. With a career spanning control theory, perception, and hardware acceleration, his research directly advances the capabilities of mobile robots in hazardous and complex settings, earning recognition for both theoretical depth and practical applicability.
Research Focus
Key Achievements
Top Papers
- 1
- 2Climbing robot for advanced high-temperature weld bead inspection9 citations · 2024
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- 5
- 6Sliding Window Mapping for Omnidirectional RGB-D Sensors2 citations · 2019