Editorial:
Special Issue on Advanced Image Processing Techniques for Robotics and Automation (Part 2)
Atsushi Yamashita*, Akio Nakamura**, and Makoto Kurumisawa***
*The University of Tokyo
Kashiwa, Chiba, Japan
**Tokyo Denki University
Adachi-ku, Tokyo, Japan
***AGC Inc.
Chiyoda-ku, Tokyo, Japan
The demand for sensing in robotics and automation has increased due to the decrease in the labor force. Recent advances in computational performance have advanced the widespread use of image processing technology in various applications. This special issue aims to provide researchers with an opportunity to access the latest research and case studies on advanced image processing, computer vision, and sensing techniques for robotics and automation. The topics of interest in this special issue are as follows:
1) Theory and algorithms: Image processing, computer vision, pattern recognition, object detection, image understanding, media understanding, machine learning, deep learning, 3D measurement, simultaneous localization and mapping (SLAM), multispectral image processing, visualization, virtual reality (VR) / augmented reality (AR) / mixed reality (MR), and datasets for image processing;
2) Industrial applications: Factory automation, machine vision, visual inspection, monitoring, surveying, logistics;
3) Sensing techniques for robotics and automation: Robot vision, advanced driver-assistance systems (ADAS), autonomous driving, robotic picking, assembly, and palletizing;
4) Image processing hardware and software: Image acquisition devices, image sensors, image processing systems, sensor information processing;
5) Man machine interface: Visualization, human interface devices.
This special issue features 20 research articles that highlight the latest advancements in advanced image processing techniques for robotics and automation (Part 1: 10 articles, Part 2: 10 articles). We extend our heartfelt gratitude to all the contributors, reviewers, and editorial staff for their dedication and support in realizing this special issue.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.