Jonay Toledo

About

Jonay Toledo is a leading researcher in autonomous robotics, specializing in sensor fusion, localization, and obstacle detection for mobile platforms. His work has significantly advanced the safety and reliability of autonomous vehicles, wheelchairs, and aerial robots. Toledo's most cited paper (52 citations) introduces a method using Kinect sensors for outdoor obstacle detection, addressing a critical challenge in autonomous navigation. He has also made notable contributions to path planning with Multiclass Support Vector Machines (29 citations) and Monte Carlo Localization with sensor fusion (16 citations), improving robot pose estimation in complex environments. His innovative approach to the forward kinematics of Stewart Platforms using artificial intelligence (16 citations) demonstrates his versatility in both mobile and parallel robotics. Toledo's recent work includes developing an augmented Kalman filter for localization with intrinsic sensor delays (2023) and applying LSTM networks to enhance odometric models (2023), showcasing his commitment to integrating machine learning with traditional robotics. With over 170 total citations, his research continues to shape the field of autonomous systems, offering practical solutions for real-world applications.

Research Focus

Key Achievements

Top Papers

1. 1
   Using Kinect on an Autonomous Vehicle for Outdoors Obstacle Detection

   52 citations · 2016
2. 2
   Path planning using a Multiclass Support Vector Machine

   29 citations · 2016
3. 3
   MCL with sensor fusion based on a weighting mechanism versus a particle generation approach

   16 citations · 2013
4. 4
   An artificial intelligence approach to forward kinematics of Stewart Platforms

   16 citations · 2012
5. 5
   Improving Robot Localization Using Doppler-Based Variable Sensor Covariance Calculation

   14 citations · 2020
6. 6
   Augmented Kalman Filter Design in a Localization System Using Onboard Sensors With Intrinsic Delays

   11 citations · 2023
7. 7
   Stability and performance analysis of unmanned aerial vehicles: Quadrotor against Hexrotor

   11 citations · 2015
8. 8
   Improving Odometric Model Performance Based on LSTM Networks

   9 citations · 2023
9. 9
   Applying an Ant Colony Optimization Algorithm to an Artificial Vision Problem in a Robotic Vehicle

   8 citations · 2008
10. 10
    A neuro-fuzzy method applied to the motors of a stereovision system

    6 citations · 2007

Key Collaborators

Contact & Links