[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127957-en":3,"doc-seo-127957-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},127957,687207024643,"Oliver","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","MACHINE LEARNING FOR ROBOT NAVIGATION CLASSIFICATION USING ULTRASOUND SENSOR DATA - Research paper","Robot navigation is a crucial aspect of robotics, enabling autonomous robots to move safely and efficiently through their surroundings. Conventionally, navigation relies on fixed rules and heuristics that often work only in specific environments and fail to adapt to new or changing conditions. This work implements machine learning to classify and improve navigation strategies using ultrasound sensor distance information. The approach supports obstacle detection and avoidance in dynamic, complex environments. Logistic regression and multilayer perceptron are highlighted as key ML techniques.","Journal of Science and Technology  \nISSN: 2456-5660 Volume 9, Issue 1 (JAN-2024)  \n [www.jst.org.in](www.jst.org.in DOI:)[ DOI:](www.jst.org.in DOI:)[https://doi.org/10.46243/jst.2024.v9.i1.pp50-60](https://doi.org/10.46243/jst.2024.v9.i1.pp50-60)   \nMACHINE LEARNING FOR ROBOT NAVIGATION CLASSIFICATION USING ULTRASOUND SENSOR DATA  \nDr. N. Baskar 1, S. Akshitha2, S. Yosmitha2, T.V. Tejaswini Yadav2  \n1Professor, 2UG Student, 1,2Department of Computer Science Engineering  \n1,2Malla Reddy Engineering College for Women, Maisammaguda, Dhulapally, Kompally,  \nSecunderabad-500100, Telangana, India  \nTo Cite this Article  \nDr. N. Baskar, S. Akshitha, S. Yosmitha, T.V. Tejaswini Yadav,“MACHINE LEARNING FOR ROBOT NAVIGATION CLASSIFICATION USING ULTRASOUND SENSOR DATA” Journal of Science and Technology, Vol. 09, Issue 01-JAN 2024, pp50-60  \nArticle Info  \nReceived: 25-12-2023 Revised: 05-01-2024 Accepted: 15-01-2024 Published: 25-01-2024  \nABSTRACT  \nRobot navigation is a crucial aspect of robotics, enabling autonomous robots to move safely and efficiently through their surroundings. Conventionally, engineers and programmers have relied on fixed rules and heuristics to guide robot movements. However, these rules are often specific to certain environments and struggle to adapt to new or changing conditions. For instance, simple obstacle avoidance techniques or path planning algorithms are commonly used. While effective in controlled settings, they lack the flexibility needed to handle diverse and unpredictable surroundings. In recent years, machine learning (ML) has emerged as a promising alternative. ML allows robots to learn from data and adjust their navigation strategies based on real-time sensory inputs. As a result, this project focuses on implementing ML for robot navigation classification, aiming to create more capable and versatile robotic systems. By utilizing this approach, robots can learn from their experiences and sensory data, improving their ability to navigate complex environments. This adaptive approach is especially valuable in scenarios where the environment undergoes frequent changes or presents diverse and challenging obstacles, beyond what traditional rule-based methods can handle. The utilization of ultrasound sensor data as input provides the robot with valuable distance information, enabling precise obstacle detection and avoidance. Furthermore, incorporating ML into robot navigation enhances their capability to handle complex real-world scenarios and dynamic environments. The use of ultrasound sensor data proves to be a valuable choice, providing crucial information for accurate obstacle detection and path planning. Ultimately, this proposed ML-based approach underscores the potential of ML techniques (i.e., logistic regression, and multilayer perceptron) in enhancing robot navigation capabilities, opening doors for more advanced and autonomous robotic systems capable of operating effectively in diverse and unpredictable environments.  \nKeywords: Ultra Sound Sensor Data, Robot Navigation, Machine Learning.  \n1. INTRODUCTION  \nJournal of Science and Technology  \nISSN: 2456-5660 Volume 9, Issue 1 (JAN-2024)  \n [www.jst.org.in](www.jst.org.in DOI:)[ DOI:](www.jst.org.in DOI:)[https://doi.org/10.46243/jst.2024.v9.i1.pp50-60](https://doi.org/10.46243/jst.2024.v9.i1.pp50-60)   \nThe rise of robotics and their gradual permeation into the field of medicine is a revolution on its own. By integrating robotic systems in the medical workspace, doctors are enabled to treat individual patients in a more efficient, safer and less morbid way. However, end-to-end automated approaches are constrained by the adaptability to unexpected situations and the poor judgment of robotic systems [1] . With ever-improving ultrasound (US) technology, US is being increasingly used in diagnosticsand interventions. Unlike other modalities like computed tomography (CT), US provides real-time dynamic physiologic information while being radiation f","cbCaidx5ocEcwEu7","https://ap.wps.com/l/cbCaidx5ocEcwEu7","pdf",987530,1,10,"English","en",105,"# ABSTRACT\n# 1. INTRODUCTION\n# 2. LITERATURE SURVEY","[{\"question\":\"Why are rule-based robot navigation methods limited in changing environments?\",\"answer\":\"Fixed heuristics tend to be environment-specific and struggle to adapt when conditions change. They also lack flexibility for diverse and unpredictable surroundings.\"},{\"question\":\"How does ultrasound sensor data support robot navigation in this approach?\",\"answer\":\"Ultrasound sensors provide distance information that enables more accurate obstacle detection and avoidance, supporting path planning decisions.\"},{\"question\":\"Which machine learning methods are proposed for improving robot navigation classification?\",\"answer\":\"The document highlights logistic regression and multilayer perceptron as ML techniques to enhance navigation capabilities.\"}]","MACHINE LEARNING FOR ROBOT NAVIGATION CLASSIFICATION USING ULTRASOUND SENSOR DATA - Research paper | PDF",1785943295,25,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"machine-learning-for-robot-navigation-classification-using-ultrasound-sensor-data-research-paper","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-for-robot-navigation-classification-using-ultrasound-sensor-data-research-paper/127957/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-23","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Why are rule-based robot navigation methods limited in changing environments?","Question",{"text":76,"@type":77},"Fixed heuristics tend to be environment-specific and struggle to adapt when conditions change. They also lack flexibility for diverse and unpredictable surroundings.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How does ultrasound sensor data support robot navigation in this approach?",{"text":81,"@type":77},"Ultrasound sensors provide distance information that enables more accurate obstacle detection and avoidance, supporting path planning decisions.",{"name":83,"@type":74,"acceptedAnswer":84},"Which machine learning methods are proposed for improving robot navigation classification?",{"text":85,"@type":77},"The document highlights logistic regression and multilayer perceptron as ML techniques to enhance navigation capabilities.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":21,"slug":134},"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":107,"slug":138},19,"General","general"]