Global and local robot navigation combination for mobile robot obstacle avoidance

Year 2023, Volume: 2 Issue: 2, 335 - 343, 27.12.2023

Zead Yosif , Basil Mahmood Saad Zaghlol Saeed

Abstract

Nowadays, robots can be seen in different areas of life. Mobile robots can perform some tasks that are too risky for a human to perform. An important issue in the mobile robot was addressed, which is driving the robot until reaches its destination. A combination of global and local mobile robot navigation has been proposed to address the challenge of dynamic obstacle avoidance. A-star is utilized to discover an initial way between the begin and goal points. The ANFIS model is called when the obstacle is near to the mobile robot to anticipate the collision.
There are three inputs and two outputs in the adaptive neurofuzzy inference system. Angle, distance, and the relative speed between the mobile robot and any obstacles are the inputs. The outputs are recommendations for a mobile robot's steering angle and speed. According to the simulation findings, the model can avoid both static and moving obstacles in a static known environment. The proposed system achieves avoiding multiple obstacles. In comparison with other papers, the proposed model shows the enhancement in path length, speed, and time required for mobile robot traveling.

Keywords

Mobile robot navigation, local path planning, global path planning, Adaptive Neuro-Fuzzy Inference System, dynamic obstacle avoidance

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