Version 1
: Received: 16 October 2023 / Approved: 16 October 2023 / Online: 16 October 2023 (11:22:30 CEST)
How to cite:
Stavrinidis, S.; Zacharia, P. Robot Collision-Free Navigation in Dynamic Environments using ANFIS. Preprints2023, 2023100964. https://doi.org/10.20944/preprints202310.0964.v1
Stavrinidis, S.; Zacharia, P. Robot Collision-Free Navigation in Dynamic Environments using ANFIS. Preprints 2023, 2023100964. https://doi.org/10.20944/preprints202310.0964.v1
Stavrinidis, S.; Zacharia, P. Robot Collision-Free Navigation in Dynamic Environments using ANFIS. Preprints2023, 2023100964. https://doi.org/10.20944/preprints202310.0964.v1
APA Style
Stavrinidis, S., & Zacharia, P. (2023). Robot Collision-Free Navigation in Dynamic Environments using ANFIS. Preprints. https://doi.org/10.20944/preprints202310.0964.v1
Chicago/Turabian Style
Stavrinidis, S. and Paraskevi Zacharia. 2023 "Robot Collision-Free Navigation in Dynamic Environments using ANFIS" Preprints. https://doi.org/10.20944/preprints202310.0964.v1
Abstract
Autonomous navigation of a mobile robot in dynamic environments presents a significant challenge in the field of robotics. The primary objective for mobile robot navigation is to ensure both smoothness and safety of movement. A path planning is applied to generate a trajectory that allows the robot to move smoothly while avoiding collisions with both stationary and moving obstacles. This study aims to introduce an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based control strategy for a mobile robot navigating in dynamic environments, with a significant focus on ensuring collision-free path planning. The developed control strategy incorporates four ANFIS controllers, each regulating the robot's responsive behaviors. The experimental scene includes a mobile robot moving in an environment with static and dynamic obstacles without colliding with the obstacles. The experimental tests confirm the model's capability to facilitate collision-free motion, employing a path planning algorithm for determining the shortest route to the target destination. Simulations are conducted to show the effectiveness of the proposed algorithm, highlighting the mobile robot's efficiency in navigating without collisions while avoiding both stationary and moving obstacles using the integration of ultrasonic sensors.
Keywords
mobile robot; path planning; ANFIS; navigation; collision avoidance
Subject
Engineering, Mechanical Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
