Bruno Marques Ferreira da Silva

About

Bruno Marques Ferreira da Silva is a robotics and computer vision researcher whose work centers on simultaneous localization and mapping (SLAM), visual odometry, and sensor-based navigation for autonomous robotic systems. Over more than a decade of research, he has made significant contributions to the development and evaluation of algorithms that enable robots to perceive, map, and navigate complex indoor and outdoor environments using RGB-D cameras and artificial markers. Among his most impactful contributions is his work on smart artificial markers for visual mapping and localization (2021, 26 citations), which advanced the accuracy of camera pose estimation in large-scale environments. His experimental evaluations of ROS-compatible SLAM algorithms (2017, 23 citations) and depth data error estimation methods for RGB-D sensors (2018, 23 citations) have become valuable references for practitioners deploying robotic systems within the Robot Operating System ecosystem. His earlier foundational work on fast visual odometry systems and feature tracking algorithms laid important groundwork for real-time robotic perception pipelines. More recently, his research has pushed toward multi-camera stereo fusion and nonlinear optimization for visual odometry (2024). With a consistent publication record spanning over a decade and accumulating more than 115 citations, da Silva has established himself as a productive contributor to the practical advancement of autonomous robot navigation.

Research Focus

Key Achievements

Top Papers

1. 1
   Smart Artificial Markers for Accurate Visual Mapping and Localization

   26 citations · 2021
2. 2
   Experimental evaluation of ROS compatible SLAM algorithms for RGB-D sensors

   23 citations · 2017
3. 3
   A Versatile Method for Depth Data Error Estimation in RGB-D Sensors

   23 citations · 2018
4. 4
   Accuracy Analysis of Augmented Reality Markers for Visual Mapping and Localization

   15 citations · 2017
5. 5
   Mapping and Navigation for Indoor Robots under ROS: An Experimental Analysis

   10 citations · 2019
6. 6
   A Fast Visual Odometry and Mapping System for RGB-D Cameras

   6 citations · 2014
7. 7
   Visual Odometry and Mapping for Indoor Environments Using RGB-D Cameras

   5 citations · 2015
8. 8
   Real-Time Localization of Mobile Robots in Indoor Environments Using a Ceiling Camera Structure

   5 citations · 2013
9. 9
   A Fast Feature Tracking Algorithm for Visual Odometry and Mapping Based on RGB-D Sensors

   3 citations · 2014
10. 10
    Nonlinearly Optimized Dual Stereo Visual Odometry Fusion

    2 citations · 2024

Key Collaborators

Contact & Links