Brain-inspired intelligent robotics: Theoretical analysis and systematic application
IMAGE: THE RESEARCHERS CONSTRUCTED A HARDWARE PLATFORM WITH THE SAME MUSCLE DISTRIBUTION AND STRUCTURE. view more
CREDIT: BEIJING ZHONGKE JOURNAL PUBLISING CO. LTD.
Robots have become a crucial indicator for measuring the competitive strength of a country in science and technology. Robotic systems have made advancements in fields such as mechanical engineering, control and artificial intelligence technologies. However, the performance of current robotic systems still exists limitations and cannot satisfy the demands of an increasing number of applications. In order to deal with these problems, a brain-inspired intelligent robotic system is constructed.
A team of scientists led by Professor Qiao Hong from the State Key Laboratory of Management and Control for Complex System, Institute of Automation, Chinese Academy of Sciences, have conducted a review on the cutting-edge works along the research chain of brain-inspired robots. Firstly, they introduce the core neural mechanisms in vision, decision-making, control, and body structure and the corresponding brain-inspired algorithm. Secondly, they present the software and hardware system integration. The simulation platform for brain-inspired robots integrates brain-inspired algorithms in vision, decision making, and movement control, providing efficient tools for researchers from different fields. The hardware platform was designed to mimic the human musculoskeletal system, providing a physical system to validate the performance of the brain-inspired algorithm.
“Brain-inspired motion-learning algorithms can use sparse rewards to realize generalized control policy learning. With this method, robotics can accomplish a series of manipulations after simple training.” “System robustness comes from redundancy and anti-interference can improve system reliability.” “The special muscle actuator provides nonlinear dynamics and coupled feedback modulation, which can reduce the effects of disturbances from the control input and environment.” They describe the advantages of the brain-inspired intelligent robotics.
Furthermore, they make assumptions about the future development of next-generation robotics. “Next-generation robotics could be developed with numerous brain-inspired algorithms and novel musculoskeletal structures.” “Organic structural design and hardware construction should be reinforced and emphasized.” “We hope that this generation of robotics can provide inspiration and reference for brain-computer interface control.” More time and efforts are supposed to be devoted to the development of the brain-inspired intelligent robotics.
See the article:
Brained-inspired Intelligent Robotics: Theoretical Analysis and Systematic Application
http://doi.org/10.1007/s11633-022-1390-8
JOURNAL
Machine Intelligence Research
ARTICLE TITLE
Brain-inspired Intelligent Robotics: Theoretical Analysis and Systematic Application
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