Papers
5
Total Citations
22
H-Index
4
About
Hazem Issa’s research lies at the intersection of robotics, adaptive control, and autonomous systems, with a particular focus on solving complex kinematic and control challenges for redundant robotic arms and driverless vehicles. His major contributions include the development of a receding horizon-type solution for the inverse kinematic task of redundant robots, which addresses the lack of closed-form solutions by employing numerical optimization over a discretized horizon. He also advanced adaptive robot control by integrating particle swarm optimization for model identification, significantly improving the robustness of model-based controllers against imprecisions and incomplete physical models. In the domain of autonomous driving, Issa designed and implemented a low-cost, retrofittable auto-driving system with collision avoidance, demonstrating practical innovation in vehicle automation. His work on the accelerated reduced gradient algorithm further enhances the efficiency of solving inverse kinematics under constraints. With over 20 citations across his most-cited papers, Issa’s research is recognized for bridging theoretical optimization techniques with real-world robotic applications, offering scalable solutions for dexterous manipulation and autonomous navigation.
Research Focus
Key Achievements
Top Papers
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