Vision is one of the most important awareness extensions that can be included in a system. With the technological advances obtained in the development of reliable artificial vision, the interactions between different autonomous systems have become more efficient and versatile.
The emerging role of machine vision in the motion planning and control of intelligent autonomous systems is one of the most discussed topics in multiple research areas (computer vision, robotics, artificial intelligence, assistive devices, etc.). Scene representation methods organize information from all sensors and data sources to build an interface between perception, navigation, and control. Stereo vision systems are among the most commonly used sensors to gather data from 3D environments. Stereo vision applications vary from autonomous driving to human–robot interactions and assisting devices for the visually impaired.
The key aim of this Special Issue is to bring together innovative research that uses off-the-shelf or custom-made stereo vision devices to extend the capabilities of intelligent autonomous systems. Contributions from all fields related to the integration of stereo vision into perception and navigation architectures are of interest, particularly including, but not limited to, the following topics:
Stereo vision for autonomous UAVs;
Stereo-vision-based collaborative perceptions for teams of mobile robots;
Stereo vision for autonomous driving;
Stereo-vision-based visual servoing;
Stereo-vision-based human–robot skill transfer;
Stereo vision perception and navigation for the visually impaired;
Stereo omnidirectional vision devices and applications;
Biologically-inspired stereo vision for robotics;
Good experimentation and reproducibility in robotic stereo systems.
Dr. Adrian Burlacu
Dr. Enric Cervera