Papers
6
Total Citations
32
H-Index
4
About
Hamid Jabbar is a pioneering researcher at the intersection of tactile sensing, robotics, and intelligent manufacturing. His work is defined by the development of bio-inspired multimodal sensors that mimic the human tactile system, enabling robots to discriminate between static and dynamic forces with remarkable sensitivity. His most cited paper (9 citations) introduces a capacitive-piezoelectric tactile force sensor that combines neural network-based texture discrimination, a breakthrough with direct applications in robot-assisted surgery and advanced prosthetics. Jabbar has also made significant contributions to autonomous navigation, proposing a Z-number-based fuzzy logic framework within ROS Noetic to handle uncertainty in mobile robot path planning (7 citations). His survey on robotic manipulation for carbon fiber reinforced polymers (6 citations) addresses a critical need in aerospace and automotive manufacturing, highlighting his impact on Industry 4.0. Additionally, his novel overtaking maneuvering algorithm using a modified Rendezvous Guidance method demonstrates his versatility in autonomous vehicle control. With a career spanning energy-efficient sensor networks and high-precision tactile sensing, Jabbar’s work consistently bridges theoretical innovation and practical deployment, earning him recognition as a key figure in modern robotics and sensor technology.
Research Focus
Key Achievements
Top Papers
- 1
- 2Z-Number-Based Fuzzy Logic Approach for Mobile Robot Navigation7 citations · 2023
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- 6A novel approach of overtaking maneuvering using modified RG method2 citations · 2022