Autonomous Intelligent Robots and Systems
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".
Deadline for manuscript submissions: closed (10 March 2024) | Viewed by 878
Special Issue Editors
Interests: intelligent robot research and development; artificial intelligence and computer application technology
Interests: plasmons; terahertz; photodetectors; object detection; CNN; IOU; electromagnetic shielding; effective bandwidth; electric network analyzers
Special Issue Information
Dear Colleagues,
At present, there are the following key problems to be solved in research into autonomous intelligent robots and systems: 1) the traditional audio-visual perception and task-control methods cannot be separated from the control of a given task, and they do not have the ability to face complex environments. 2) The existing AI methods cannot effectively and comprehensively solve the main problems faced by visual perception, task control, and deep learning. 3) The existing audio-visual perception methods need to be improved in feature extraction and learning efficiency, which can be effectively solved by high-performance computing. 4) In the research of existing visual perception methods, convolution neural networks (CNNs), the residual neural network (ResNet), and the dense connection network (DenseNet) are commonly used for image recognition, face recognition, image semantic segmentation, etc. With the expansion of the convolution network parameters and the update of the network structure, its training cost is also greatly increased. 5) The existing dexterous hand operation control method basically controls the position and force feedback or impedance of the finger equipped with independent force/torque sensors at the fingertips of the hand. None of the control methods consider or control the contact force of many tactile points on the surface of fingers and palms. The existing control methods of the autonomous robots and systems make it difficult to effectively solve the above problems. Therefore, it is very urgent to study the characteristics, requirements, and limitations of audio-visual perception and task-control methods of the autonomous robots and systems so as to further improve the ability of the autonomous robots and systems in completing various tasks.
Prof. Dr. Nanfeng Xiao
Prof. Dr. Guangcun Shan
Guest Editors
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Keywords
- autonomous intelligent robots and systems
- audio-visual perception
- task control methods
- deep learning
- high-performance computing
- dexterous hands
- force/torque control methods
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