Three-State Multirobot CollaborativeLocalization in Symmetrical Environments

Abstract In this paper, we present HoloSLAM which is a novel solution to landmark detection issues in the simultaneous localization and mapping (SLAM) problem in autonomous robot navigation. The approach integrates real and virtual worlds to create a novel mapping robotic environment employing a mixed-reality technique and a sensor, namely Microsoft HoloLens. The proposed methodology allows the robot to interact and communicate with its new environment in real-time and overcome the limitations of conventional landmark-based SLAMs by creating and placing some virtual landmarks in situations where real landmarks are scarce, non-existent, or hard to be detected. The proposed approach enhances the robot’s perception and navigation capabilities in various robot environments. The overall process contributes to the robot’s more accurate understanding of its environment; thus, enabling it to navigate with greater efficiency and effectiveness. In addition, the newly implemented HoloSLAM offers the option to guide the robot to a specific location eliminating the need for explicit navigation instructions. The open-source framework proposed in this paper can benefit the robotics community by providing a more reliable, realistic, and robust mapping solution. The experiments show that the Ellipsoidal-HoloSLAM system is accurate and effectively overcomes the limitations of conventional Ellipsoidal-SLAMs, providing a more precise and detailed mapping of the robot’s environment. 

HoloSLAM: a novel approach to virtual landmark-based SLAM for indoor environments

In this work we address different techniques for autonomous navigation of single and multi-robot systems in unstructured indoor environments. The first problem that we address is the problem of robot localization. We first show how a multi-robot localization approach can speed up the process as well as introducing robustness to failures. At the same time we show the possibility to introduce some sort of insight into the algorithm. We then focus on increasing the robustness of single robot localization, by taking advantage of sensor fusion and by exploiting visual markers embedded in the environment. We then show how the approach can be extended from ad-hoc markers to an arbitrary set of pre-existing objects already present in the environment. Then we address the more complicated problem of Simultaneous Localization and Mapping. In particular we focus on a promising technique called Graph-SLAM and we show the implementation of a front-end for this optimization technique in order to create a real online SLAM approach. The last part of the thesis is devoted to another part of service robotics which is not directly related to navigation: Human Robot Interaction (HRI). While this field of robotics is not strictly related to autonomous navigation, some part of it can be, such as the case of user following and object tracking. In Chapter 4 we discuss the implementation of an adaptive people tracking algorithm tailored for user tracking and following. We also show how this algorithm can easily be extended to the case of generic object tracking for human-robot cooperation

Localization and Mapping for Service Robotics Applications

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Stefano Rosa

Author Tools

Chat about Author

Papers

Localization and Mapping for Service Robotics Applications