E.E. Eldukhri

About

E.E. Eldukhri is a robotics and intelligent systems researcher whose work sits at the intersection of bio-inspired optimization, fuzzy logic control, and autonomous robotic systems. Best known for pioneering applications of the Bees Algorithm to robotics control, Eldukhri has made significant contributions to the challenging problem of stabilizing underactuated robotic systems. His most cited work (52 citations) demonstrated how the Bees Algorithm could effectively tune fuzzy logic controllers to balance the notoriously difficult ACROBOT — a two-link gymnastic robot — in an upright position, building upon an earlier foundational study from 2007 that garnered 37 citations. This thread of research extended to the more complex three-link Robogymnast system, tackling both swing-up and balancing control through techniques including discrete-time Linear Quadratic Regulation. Beyond gymnastic robotics, Eldukhri has contributed to cooperative multi-agent robot systems, adaptive neuro-fuzzy modeling, automated gripper configuration for assembly tasks, and biped locomotion control. His early work on an eight-degree-of-freedom walking biped at the University of Salford reflects a career-long commitment to advancing practical autonomous systems. Collectively, his publications have attracted over 180 citations, establishing him as a distinctive voice in intelligent robotic control research.

Research Focus

Key Achievements

Top Papers

1. 1
   Optimisation of a fuzzy logic controller using the Bees Algorithm

   52 citations · 2009
2. 2
   Using the Bees Algorithm to tune a fuzzy logic controller for a robot gymnast

   37 citations · 2007
3. 3
   Optimisation of swing-up control parameters for a robot gymnast using the Bees Algorithm

   18 citations · 2013
4. 4
   Autonomous Swing-Up Control of a Three-Link Robot Gymnast

   16 citations · 2010
5. 5
   Automated configuration of gripper systems for assembly tasks

   15 citations · 2007
6. 6
   Balancing Control of Robot Gymnast Based on Discrete-Time Linear Quadratic Regulator Technique

   14 citations · 2014
7. 7
   Biped robot locomotion in the sagittal I plane

   11 citations · 1997
8. 8
   Adaptive and cooperative mobile robots

   6 citations · 2007
9. 9
   ADAPTIVE FUZZY NEURAL NETWORK FOR INVERSE MODELING OF ROBOT MANIPULATORS

   6 citations · 2008
10. 10
    Fuzzy and Neuro-fuzzy Based Co-operative Mobile robots

    5 citations · 2006

Key Collaborators

Contact & Links