Ekaitz Zulueta

About

Ekaitz Zulueta is a robotics researcher whose work bridges autonomous navigation, multi-agent coordination, and intelligent control systems. His most impactful contributions focus on improving mobile robot mobility and decision-making. In his highly cited 2019 paper (44 citations), he developed a Predictive Dynamic Window Approach enhanced with an Artificial Neural Fuzzy Inference System, enabling robots to adapt their movement parameters in real time to surrounding conditions—a significant advance for dynamic environments. His 2020 work (43 citations) introduced a semantic segmentation network using residual neural networks for indoor navigation, allowing robots to understand and traverse complex indoor spaces autonomously. Earlier, Zulueta pioneered research on Linked Multi-Component Robotic Systems (L-MCRS), exploring how multiple robots can collaboratively transport a passive, flexible hose—a challenging problem involving nonlinear dynamics. His foundational 2011 paper (16 citations) established key principles for this domain, while subsequent studies applied Q-learning to train multi-agent systems for hose transport control. With over 150 total citations, Zulueta’s work has practical implications for warehouse automation, disaster response, and service robotics, demonstrating how fuzzy logic, deep learning, and reinforcement learning can create more adaptive, cooperative robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Predictive Dynamic Window Approach Development with Artificial Neural Fuzzy Inference Improvement

   44 citations · 2019
2. 2
   Semantic Segmentation to Develop an Indoor Navigation System for an Autonomous Mobile Robot

   43 citations · 2020
3. 3
   Basic Results and Experiments on Robotic Multi-Agent System for Hose Deployment and Transportation

   16 citations · 2011
4. 4
   IMPROVING THE CONTROL OF SINGLE ROBOT HOSE TRANSPORT

   12 citations · 2012
5. 5
   Linked Multicomponent Robotic Systems: Basic Assessment of Linking Element Dynamical Effect

   10 citations · 2010
6. 6
   Empirical Study of Q-Learning Based Elemental Hose Transport Control

   9 citations · 2011
7. 7
   Training Multiagent Systems by Q‐Learning: Approaches and Empirical Results

   7 citations · 2014
8. 8
   Lattice Independent Component Analysis for Mobile Robot Localization

   6 citations · 2010
9. 9
   Economical Implementation of Control Loops for Multi-robot Systems

   5 citations · 2009
10. 10
    On Distributed Cooperative Control for the Manipulation of a Hose by a Multirobot System

    5 citations · 2008

Key Collaborators

Contact & Links