Zayed Alsalem
Papers
1
Total Citations
3
H-Index
1
About
Zayed Alsalem is a researcher at the forefront of human-robot interaction (HRI) and assistive robotics, with a focus on developing intuitive, real-time control systems. His most-cited work, "Integrating Human Hand Gestures with Vision Based Feedback Controller to Navigate a Virtual Robotic Arm" (2020), introduces a novel hybrid control algorithm that fuses inertial measurement unit (IMU) data from a Myo Gesture Control Armband with vision-based feedback to precisely operate a 6-DOF Kinova virtual robotic arm. This contribution bridges the gap between wearable gesture recognition and visual servoing, enabling more natural and responsive manipulation for applications in rehabilitation and teleoperation. With 3 citations, this paper lays foundational groundwork for accessible robotic interfaces. Alsalem’s research addresses critical challenges in HRI, including sensor fusion and real-time feedback control, aiming to empower individuals with motor impairments. His work exemplifies a commitment to advancing human-centered robotics through innovative, low-cost solutions that enhance user autonomy and interaction fidelity.
Research Focus
Key Achievements
Top Papers
- 1