Navigational Analysis of Legged Robot using the Modified African Vulture Optimization Algorithm

Navigational Analysis of Legged Robot using the Modified African Vulture Optimization Algorithm | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Navigational Analysis of Legged Robot using the Modified African Vulture Optimization Algorithm Pinaki Das, Dayal R. Parhi, Abhijit Mahapatro, Himansu Sekhar Dash, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6004194/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The main challenges in the legged robot are navigation, obstacle avoidance, and path development. This study uses a swarm intelligence based meta-heuristic technique the Modified African Vulture Optimization Algorithm (MAVOA), to address the optimum path planning problem. The developed algorithm imitates the foraging behaviour of vultures. The MAVOA dynamically adjusts the movement of vultures to equate exploration and exploitation. This technique is selected to get the optimum path by avoiding obstacles while navigating a legged robot in an unfamiliar, congested environment. When it comes to the legged robot navigation, the path planning problem is solved by selecting four governing constraints: front-side hurdle length (FHL), left-side hurdle length (LHL), right-side hurdle length (RHL), and the direction of turn (DT) that are considered as the inputs and outputs respectively. The main constraints of earlier researches on existing techniques are impotence to account for motion in new environments, challenges in navigating crowded and complex areas, and the need to optimize intricate pathways. The WEBOT software is chosen for simulating a navigation of a legged robot, and result of simulation is differentiated to experimental outputs configured in a lab setting. Both outcomes show that the legged robot successfully navigated to its objectives while avoiding impediments. After the findings were assessed, it was found that there was less than 5% difference between the output of the simulation and the experiment. The approach can be applied to multiple-purpose or discrete optimization issues and future complicated engineering and science disciplines. Hurdles Legged Robot MAVOA Navigation Simulation WEBOT Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6004194","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":414730239,"identity":"af3a67d7-fe62-4762-adb0-fbb826e7c274","order_by":0,"name":"Pinaki Das","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIie2RsUrEQBRFbzXbPEw7i5L9hQcBRVjwVyYsThXEcstUm2Y/YD/D0sLihUCq+QCXbUyzNgqxU9jCSRAbcbawsZhTDfPe4d5hgEjkH3JVVQKwJjUp4U/mbLw2AYXJ+fHtPD0hgQgMHVe0YaC3War92rcS4gLm+q7nJl9NX+vm7cESJs0TuvvflcuybrebQTm9MSL7gkCWkbtATF3aHY1KwSKy9MUKIF8FlAbnu8NYzH0pyUtY4dYrYJspTYPii+kjKdM12e2a56kiX8yJJaX3LCElmT23j+8HTbPKZf1SFmmSLLruI/SWHygM/xOJRCKRP/EJaeRXX6rO8BsAAAAASUVORK5CYII=","orcid":"","institution":"National Institute of Technology","correspondingAuthor":true,"prefix":"","firstName":"Pinaki","middleName":"","lastName":"Das","suffix":""},{"id":414730240,"identity":"f1b97649-0c2d-45c6-b7c4-5079227c8c63","order_by":1,"name":"Dayal R. 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