Advances in Robot Vision Perception and Control Technology

Dear Colleagues,

Over the past few decades, the robotics industry has witnessed incredible growth. The robotics market, in particular, the autonomous robots market, will continue to expand at remarkable speed. Unlike traditional robotic manipulators, which perform labor-intensive tasks in structured factory settings, modern robots are required to work alongside human beings. In order to succeed in these uncontrolled settings, modern robots must have the ability to understand the surrounding environment and control their actions without continuous human intervention. In other words, robotic perception and control play a vital role for autonomous robots in unstructured human environments. Similar to human eyes, cameras provide a robot with abundant information, allowing the robot to understand its location, detect obstacles, find objects of interest, etc. While promising, robot vision perception and control are underexplored topics, and there remain numerous technical challenges to address. The following Topic provides researchers with a platform to share their research insights on the theoretical analysis and applications of robot vision in practical experiments. Topics of interest include, but are not limited to:

• Visual SLAM
• Visual odometry
• Visual serving
• Visual tracking
• Vision-based object detection
• Machine learning techniques with application to robot vision
• Vision-based obstacle avoidance
• Vision-based robotic manipulation
• Computer vision with application to robotics

Dr. Yugang Liu
Prof. Dr. Sidney Givigi
Topic Editors