Theory and Applications of Bioinspired Neural Intelligence for Robotics and Control
1University of Guelph, Guelph, Canada
2University of Detroit Mercy, Detroit, USA
3University of New Brunswick, Fredericton, Canada
4Hohai University, Nanjing, China
5University of Hamburg, Hamburg, Germany
Theory and Applications of Bioinspired Neural Intelligence for Robotics and Control
Description
Research on computational intelligence and neuroscience, particularly bioinspired intelligence, has made significant progress in both understanding the neuroscience and biological systems, and applying to various robotic and control systems. This special issue is devoted to new activities in intelligent robotics and control systems with emphasis on humanoid robots and bioinspired robotics, where the methodologies for the robotic systems are mainly inspired from the strategies, mechanisms, and functionality of neural systems and biological systems, e.g., biologically-inspired neural networks, genetic algorithms, and fuzzy systems. The focus of this issue will be to present several theoretical and practical problems related to robotics and control system, particularly with bioinspired intelligence approaches.
Papers are solicited for the special issue of Computational Intelligence and Neuroscience covering research results as well as case studies and applications in related areas of interest.
Potential topics include, but are not limited to:
- The biological fundamentals of bioinspired intelligence approaches
- Optimization mechanism on bioinspired intelligence approaches
- Performance measurements of bioinspired intelligence approaches
- Stability and convergence of bioinspired intelligence approaches
- Bioinspired trajectory generation and motion planning of robotic systems
- Bioinspired path tracking and motion control of robotic systems
- Intelligent cooperation and coordination of multirobots
- Intelligence approaches for uncertainty handling in robotics and control system
- Intelligence approaches for multisensor fusion in robotics and control systems
- Intelligence approaches for machine vision in robotics and control system