Computer Vision in Robotic Manipulation
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 April 2026
Special Issue Editors
Interests: robotic manipulation of low-stiffness components based on tactile sensing; safety-oriented operation technology for specialized robots; control methods for medical assistive puncture robots
Interests: perception and autonomous navigation and localization of robots; motion control and machine learning of robots; creation and optimization design of new robots
Interests: motion planning for robotic arms and coordinated motion planning for dual arms; intelligent control and interaction technology under human-machine integration; intelligent detection technology for special aerospace components; development technology for intelligent systems based on embedded microcontrollers; 3D visual point cloud feature extraction and reconstruction technology
Special Issue Information
Dear Colleagues,
Robotic manipulation has become a cornerstone of intelligent manufacturing, service robotics, and human–robot collaboration. With the rapid development of artificial intelligence, computer vision has emerged as a crucial enabling technology, providing robots with the ability to perceive, interpret, and interact with complex and dynamic environments. Vision-guided manipulation enables robots to perform tasks that require high precision, adaptability, and autonomy, ranging from industrial assembly and logistics to healthcare and assistive applications.
This Special Issue aims to bring together recent advances in computer vision methods and their integration into robotic manipulation. Topics of interest include innovative perception algorithms, vision-based grasping and manipulation strategies, multimodal sensor fusion, learning-based control, and real-time vision systems for dynamic and unstructured scenarios. Research contributions addressing challenges such as robustness, generalization, scalability, and human–robot safety are also highly encouraged. Both original research articles and comprehensive reviews are welcome, covering theory, algorithms, system implementations, and real-world applications.
Through this Special Issue, we seek to highlight cutting-edge progress in computer vision technologies that enhance the intelligence, versatility, and efficiency of robotic manipulation, paving the way for next-generation autonomous robotic systems.
Prof. Dr. Changle Li
Dr. Jie Chen
Dr. Hui Zhang
Guest Editors
Manuscript Submission Information
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Keywords
- computer vision for robotics
- vision-based robotic manipulation
- grasp detection and planning
- deep learning for robotic perception
- visual servoing and control
- multimodal sensor fusion
- real-time object recognition and tracking
- human–robot collaboration
- intelligent manufacturing automation
- vision-guided autonomous systems
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