Andry Maykol Pinto

About

Andry Maykol Pinto is a leading researcher in robotics and autonomous systems, with a focus on perception, localization, and safety for unmanned vehicles. His work spans underwater, aerial, and surface robotics, as well as cable-driven construction robots. Pinto’s major contributions include developing the MARESye hybrid imaging system for underwater robotic applications, which has garnered 53 citations, and advancing object recognition techniques using laser range finders and machine learning (54 citations). He has also pioneered localization methods based on map-matching and particle swarm optimization (35 citations), and created ArTuga, a novel multimodal fiducial marker for precise VTOL UAV landing (32 citations). His research on 3D perception for autonomous surface vehicles (35 citations) and depth sensor evaluation (26 citations) has significantly impacted maritime and industrial automation. Pinto’s work on safety monitoring for faulty mobile robots (21 citations) and cable-driven robots for architectural construction (35 and 21 citations) demonstrates his commitment to robust, real-world applications. With over 300 citations across his most-cited works, Pinto’s contributions are driving the evolution of fully autonomous systems in challenging environments, from deep sea to construction sites.

Research Focus

Key Achievements

Top Papers

1. 1
   Object recognition using laser range finder and machine learning techniques

   54 citations · 2012
2. 2
   MARESye: A hybrid imaging system for underwater robotic applications

   53 citations · 2019
3. 3
   A Localization Method Based on Map-Matching and Particle Swarm Optimization

   35 citations · 2013
4. 4
   A cable-driven robot for architectural constructions: a visual-guided approach for motion control and path-planning

   35 citations · 2016
5. 5
   Advancing Autonomous Surface Vehicles: A 3D Perception System for the Recognition and Assessment of Docking-Based Structures

   35 citations · 2021
6. 6
   ArTuga: A novel multimodal fiducial marker for aerial robotics

   32 citations · 2023
7. 7
   Evaluation of Depth Sensors for Robotic Applications

   26 citations · 2015
8. 8
   Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor

   21 citations · 2016
9. 9
   The SPIDERobot: A Cable-Robot System for On-site Construction in Architecture

   21 citations · 2016
10. 10
    A Safety Monitoring Model for a Faulty Mobile Robot

    21 citations · 2018

Key Collaborators

Contact & Links