Tiago Madeira
Papers
3
Total Citations
38
H-Index
3
About
Tiago Madeira is a robotics researcher whose work centers on sensor calibration for intelligent vehicles and autonomous systems. His primary contributions lie in developing robust, multi-modal extrinsic calibration frameworks that enable precise alignment of diverse sensors—such as lidar, cameras, and inertial units—within a unified coordinate system. Madeira’s most cited paper, "A ROS framework for the extrinsic calibration of intelligent vehicles: A multi-sensor, multi-modal approach" (2020), has garnered 23 citations, reflecting its practical utility in the robotics community. This work builds on his earlier 2019 paper (9 citations), which introduced a general calibration approach using the Robot Operating System (ROS). Notably, his 2020 study on "2D lidar to kinematic chain calibration using planar features of indoor scenes" (6 citations) addresses a specific challenge: integrating 2D laser rangefinders with mechanical units that add degrees of freedom, enabling accurate range measurements in dynamic environments. Madeira’s research bridges theory and application, offering accessible, open-source solutions that advance the reliability of perception systems for autonomous navigation. His work is particularly valuable for students and engineers seeking practical calibration methods for multi-sensor robotic platforms.
Research Focus
Key Achievements
Top Papers
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