A survey on vision guided robotic systems with intelligent control strategies for autonomous tasks

Abstract

The Vision Guided Robotic systems (VGR) is an essential aspect of modern intelligent robotics. The VGR is rapidly transforming manufacturing processes by enabling robots to be highly adaptable and intelligent reducing the cost and complexity. For any sensor-based intelligent robots, vision-based planning is considered as one of the most prominent steps followed by controlled actions using visual feedback. To develop robust vision-based autonomous systems in robotic applications, path-planning and localization can be implemented along with Visual Servoing (VS) for robust feedback control. In the available literature, most of the reviews are focused on a particular module of autonomous systems like path planning, motion planning strategies, or Visual Servoing techniques. In this paper overall review of different modules in vision-guided robotic systems is presented. So, this review provides researchers with broader in-depth knowledge about different modules that exist in the vision-guided autonomous system. The review also includes different vision sensors that are commonly used in industries covering their characteristics and applications. In this work, overall, 227 research papers in path planning and vision-based control algorithms are reviewed with recent intelligent techniques based on optimization and learning-based approaches. The graphical analysis illustrating the advancements of research in the field of vision-based robotics using Artificial Intelligence (AI) is also discussed. Lastly, this paper concludes by discussing some of the research gaps, challenges, and future directions existing in vision-based planning and control.

Keywords

• path planning
• visual servoing
• vision guided robotic systems
• vision sensors
• control techniques
• artificial intelligence