Papers
8
Total Citations
76
H-Index
5
About
Issa Ahmed Abed is a robotics researcher whose work lies at the intersection of autonomous navigation, bio-inspired design, and optimization algorithms. His primary contributions focus on solving critical challenges in mobile robotics—particularly path planning and trajectory tracking for two-wheeled robots—and in manipulator control, where he has advanced solutions for inverse kinematics and task scheduling. Abed’s most cited paper (2023, 27 citations) presents a comprehensive framework for collision-free navigation and trajectory tracking, addressing the real-time demands of autonomous operation. He has also pioneered hybrid optimization techniques, such as combining Grey Wolf Optimizer with Particle Swarm Optimization (GWO-PSO) for robot path planning (2022, 11 citations), and has extensively compared and modified algorithms like the Electromagnetism-Like Algorithm (EM) and Genetic Algorithm (GA) for dual-manipulator scheduling and inverse kinematics (2014, 13 citations). Notably, Abed’s work extends to soft robotics, where he designed a vision-based soft mobile robot inspired by the silkworm’s body and movement (2023, 4 citations), demonstrating his versatility. With a career spanning over a decade, his research has accumulated significant impact, offering practical, optimized solutions that push the boundaries of autonomous and intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Path Planning and Trajectory Tracking Control for Two-Wheel Mobile Robot27 citations · 2023
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- 3New robot path planning optimization using hybrid GWO-PSO algorithm11 citations · 2022
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