Josafat Delfin

About

Josafat Delfin is a robotics researcher whose work bridges advanced control theory and humanoid robot autonomy. His most impactful contribution lies in the development of **predefined-time convergence control**, a powerful framework for high-order integrator systems that guarantees system stabilization within a user-specified settling time, independent of initial conditions. This work, published in 2017, has garnered **159 citations**, reflecting its significance in the control systems community. Delfin’s research also focuses on **vision-based navigation for humanoid robots**, where he has pioneered methods for visual path following and visual servo walking control. His approaches enable humanoids to navigate complex environments using monocular cameras and sequences of target images, achieving finite-time convergence and smooth velocity profiles. Notable achievements include strategies for **humanoid localization and navigation using visual memory**, as well as active techniques for simultaneous 3D object localization and reconstruction. Through these contributions, Delfin has advanced the practical deployment of humanoid robots in real-world settings, making his work essential reading for researchers in robotics, control theory, and autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Predefined-Time Convergence Control for High-Order Integrator Systems Using Time Base Generators

   159 citations · 2017
2. 2
   Visual path following using a sequence of target images and smooth robot velocities for humanoid navigation

   16 citations · 2014
3. 3
   Visual servo walking control for humanoids with finite-time convergence and smooth robot velocities

   12 citations · 2015
4. 4
   Humanoid localization and navigation using a visual memory

   7 citations · 2016
5. 5
   An active strategy for the simultaneous localization and reconstruction of a 3D object from a humanoid platform

   3 citations · 2012

Key Collaborators

Contact & Links