Hong Qiao, Ya-Xiong Wu, Shan-Lin Zhong, Pei-Jie Yin, Jia-Hao Chen. Brain-inspired Intelligent Robotics: Theoretical Analysis and Systematic Application[J]. Machine Intelligence Research, 2023, 20(1): 1-18. DOI: 10.1007/s11633-022-1390-8
Citation: Hong Qiao, Ya-Xiong Wu, Shan-Lin Zhong, Pei-Jie Yin, Jia-Hao Chen. Brain-inspired Intelligent Robotics: Theoretical Analysis and Systematic Application[J]. Machine Intelligence Research, 2023, 20(1): 1-18. DOI: 10.1007/s11633-022-1390-8

Brain-inspired Intelligent Robotics: Theoretical Analysis and Systematic Application

  • Traditional joint-link robots have been widely used in production lines because of their high precision for single tasks. With the development of the manufacturing and service industries, the requirement for the comprehensive performance of robotics is growing. Numerous types of bio-inspired robotics have been investigated to realize human-like motion control and manipulation. A study route from inner mechanisms to external structures is proposed to imitate humans and animals better. With this idea, a brain-inspired intelligent robotic system is constructed that contains visual cognition, decision-making, motion control, and musculoskeletal structures. This paper reviews cutting-edge research in brain-inspired visual cognition, decision-making, motion control, and musculoskeletal systems. Two software systems and a corresponding hardware system are established, aiming at the verification and applications of next-generation brain-inspired musculoskeletal robots.
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