Hybrid Genetic Neuro-Fuzzy Systems for Robotic Navigation and Control
Several highly intelligent robots have currently been established for the modern World. In specific, smart robotics will start to carry out activities in different areas like homes, retail, and public facilities. A smart robot can gather environmental knowledge via CCTV and/or sensors evaluate the information gathered and schedule its travel, perform the travel scheduled by preventing online crashes with the barrier. As well as several researchers have implemented the theory of soft computing in many of the following fields of study. This paper evaluates the performance analysis of robotics-based on soft computing techniques of hybrid genetic-fuzzy and deep neuro-fuzzy systems. Thus the hybrid techniques of soft computing help to improve the performance of learning, adaptation, control, and navigation of smart robotics.
Robotic Navigation and Control Systems, Genetic-Fuzzy, Deep Neuro-Fuzzy Systems
Volume 6 | Issue 1