An ANFIS-Based Strategy for Autonomous Robot Collision-Free Navigation in Dynamic Environments
Year: 2024
Type: article
Abstract: Autonomous navigation in dynamic environments is a significant challenge in robotics. The primary goals are to ensure smooth and safe movement. This study introduces a control strategy based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). It enhances autonomous robot navigation in dynamic environments with a focus on collision-free path planning. The strategy uses a path-planning technique to develop a trajectory that allows the robot to navigate smoothly while avoiding both static and dynamic obstacles. The developed control system incorporates four ANFIS controllers: two are tasked with guiding the robot toward its end point, and the other two are activated for obstacle avoidance. The experimental setup conducted in CoppeliaSim involves a mobile robot equipped with ultrasonic sensors navigating in an environment with static and dynamic obstacles. Simulation experiments are conducted to demonstrate the model’s capability in ensuring collision-free navigation, employing a path-planning algorithm to ascertain the shortest route to the target destination. The simulation results highlight the superiority of the ANFIS-based approach over conventional methods, particularly in terms of computational efficiency and navigational smoothness.
Source: Robotics
Authors: Stavros Stavrinidis, Paraskevi Zacharia
Institution: University of West Attica
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,046
OpenAlex ID: W4401751515