Fuzzy Inference System Assisted Human Aware Navigation Framework Based On Enhanced Potential Field
DOWNLOAD
Download Fuzzy Inference System Assisted Human Aware Navigation Framework Based On Enhanced Potential Field PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Fuzzy Inference System Assisted Human Aware Navigation Framework Based On Enhanced Potential Field book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Fuzzy Inference System Assisted Human Aware Navigation Framework Based On Enhanced Potential Field
DOWNLOAD
Author : Shurendher Kumar Sampathkumar
language : en
Publisher: OAE Publishing Inc.
Release Date : 2024-01-13
Fuzzy Inference System Assisted Human Aware Navigation Framework Based On Enhanced Potential Field written by Shurendher Kumar Sampathkumar and has been published by OAE Publishing Inc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-13 with Technology & Engineering categories.
With the advent of Autonomous Mobile Robots (AMRs) in public areas such as malls and airports, their harmonious coexistence with humans is crucial. AMRs must operate in a manner that ensures human safety, comfort, and acceptability to reduce stress. This is called Human Aware Navigation. This study introduces a framework for AMR navigation that prioritizes safety and human comfort in such environments, utilizing an enhanced Potential Field approach augmented by Fuzzy Inference Systems. To achieve a smooth AMR trajectory, the framework employs these systems based on AMR, human, and obstacle information. The proposed approach is tested across various scenarios, including complex, cluttered environments that mimic practical situations. Simulation results demonstrate that AMRs using the proposed method navigate human-rich environments safely and comfortably while mitigating common issues associated with Potential Field-based approaches, such as local minima and obstacles near the goal.