Design of mobile robot navigation controller using neuro-fuzzy logic system

To be successful, autonomous navigation must overcome challenges associated with the functions such as detecting perception, current location, planning, and regulating movements. It is possible to have a purposeful and reactive navigational approach. Robots and humans working in the same area must comply with safety laws regarding navigation. As a result, mobile robots in organized environments now have a navigation controller that can operate in reactive and deliberative approaches. Therefore, a neuro-fuzzy system is introduced to explore the benefits of both deliberative and reactive navigation control. It combines neural networks with a fuzzy logic controller and is used to investigate various strategies and give the robot corrective decisional commands. An amigo Bot equipped with a Kinect sensor is used to test the proposed approach in conjunction with the Virtual Robot Experimentation Platform (V-REP) and ROS Groovy Galapagos.

Automated summary

To achieve successful autonomous navigation, challenges related to perception, localization, planning, and control functions must be addressed. The introduction of a neuro-fuzzy system explores the benefits of both deliberate and reactive navigation control.