Aicha Belalia

Papers

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About

Dr. Aicha Belalia is a researcher at the forefront of robotics and computer vision, with a focused expertise in trajectory planning and control for robotic manipulators. Her most-cited work, "Trajectory Tracking of a Robot Arm Using Image Sequences," introduces a novel hybrid method that fuses deep learning with classical interpolation techniques. Specifically, she combines Convolutional Neural Networks (CNNs) for robust visual perception with Spline3 interpolation to generate smooth, precise motion paths from image data. This innovative approach allows a robot arm to accurately track and replicate trajectories derived directly from visual sequences, bridging the gap between perception and action. While her work is early-stage, with this key paper accumulating 4 citations, it signals a promising direction for integrating AI with traditional control systems. Dr. Belalia’s contribution lies in demonstrating how deep learning can enhance the adaptability of robotic systems in dynamic environments, offering a scalable solution for tasks ranging from automated assembly to assistive robotics. Her research is a valuable stepping stone for students and engineers seeking to understand the practical fusion of computer vision and robotic control.