Adriano M. C. Rezende
Papers
11
Total Citations
284
H-Index
7
About
Adriano M. C. Rezende is a leading roboticist specializing in autonomous navigation, localization, and control for robots operating in confined and geometrically challenging environments. His most impactful contribution is **EKF-LOAM**, an adaptive LiDAR SLAM framework that fuses wheel odometry and inertial data to achieve precise localization in spaces with few geometric features—a critical advancement for industrial inspection robots. This work has garnered **107 citations**, underscoring its influence. Rezende also pioneered **constructive time-varying vector fields** for robot navigation, enabling robust curve tracking and obstacle avoidance in dynamic settings (53 citations). His flagship platform, the **EspeleoRobô**, demonstrates semi-autonomous inspection and mapping in pipes, caves, and dam galleries, directly addressing hazardous manual inspection tasks. Beyond hardware, Rezende has developed integrated solutions for autonomous drone racing and low-cost pipe inspection systems, showcasing versatility. With over **280 total citations** across his top works, his research bridges theoretical control strategies and practical deployment, making him a key figure in field robotics for confined spaces.
Research Focus
Key Achievements
Top Papers
- 1
- 2Constructive Time-Varying Vector Fields for Robot Navigation53 citations · 2021
- 3
- 4Robust quadcopter control with artificial vector fields21 citations · 2020
- 5
- 6Vector field for curve tracking with obstacle avoidance17 citations · 2022
- 7
- 8
- 9Robotic Pipe Inspection: Low-Cost Device and Navigation System3 citations · 2024
- 10Safe coordination of robots in cyclic paths3 citations · 2020