MPMarius Pandelea

Marius Pandelea

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article

Previous Organizations / Institutes

The organizations / institutes from the scholar's other articles in the past ten years


Marius Pandelea has a total of 8 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Hybrid HQ Stereo Cameras and RPLIDAR Sensor System Applied to Navigation of the Autonomous Mobile Robots

    by Luige Vladareanu, Hongbo Wang, Marius Pandelea, Victor Vladareanu, Ionel-Alexandru Gal, Ștefan Ghibanu


  • Open Access

    Distance Assessment by Object Detection—For Visually Impaired Assistive Mechatronic System

    by Ciprian Dragne, Isabela Todiriţe, Mihaiela Iliescu, Marius Pandelea

    Techniques for the detection and recognition of objects have experienced continuous development over recent years, as their application and benefits are so very obvious. Whether they are involved in driving a car, environment surveillance and security, or assistive living for people with different disabilities, not to mention advanced robotic surgery, these techniques are almost indispensable. This article presents the research results of a distance assessment using object detection and recognition techniques. The first is a new technique based on low-cost photo cameras and special sign detection. The second is a classic approach based on a LIDAR sensor and an HQ photo camera. Its novelty, in this case, consists of the concept and prototype of the hardware subsystem for high-precision distance measurement, as well as fast and accurate object recognition. The experimentally obtained results are used for the motion control strategy (directional inverse kinematics) of the robotic arm (virtual prototype) component in special assistive devices designed for visually impaired persons. The advantages of the original technical solution, experimentally validated by a prototype system with modern equipment, are the precision and the short time required for the identification and recognition of objects at relatively short distances. The research results obtained, in both the real and virtual experiments, stand as a basis for the further development of the visually impaired mechatronic system prototype using additional ultrasonic sensors, stereoscopic or multiple cameras, and the implementation of machine-learning models for safety-critical tasks.