A Multistage Framework for Autonomous Robotic Mapping with Targeted Metrics

High-quality maps are pertinent to performing tasks requiring precision interaction with the environment. Current challenges with creating a high-precision map come from the need for both high pose accuracy and scan accuracy, and the goal of reliable autonomous performance of the task. In this paper...

Full description

Bibliographic Details
Main Authors: William Smith, Yongming Qin, Siddharth Singh, Hudson Burke, Tomonari Furukawa, Gamini Dissanayake
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Robotics
Subjects:
Online Access:https://www.mdpi.com/2218-6581/12/2/39
_version_ 1797603565633536000
author William Smith
Yongming Qin
Siddharth Singh
Hudson Burke
Tomonari Furukawa
Gamini Dissanayake
author_facet William Smith
Yongming Qin
Siddharth Singh
Hudson Burke
Tomonari Furukawa
Gamini Dissanayake
author_sort William Smith
collection DOAJ
description High-quality maps are pertinent to performing tasks requiring precision interaction with the environment. Current challenges with creating a high-precision map come from the need for both high pose accuracy and scan accuracy, and the goal of reliable autonomous performance of the task. In this paper, we propose a multistage framework to create a high-precision map of an environment which satisfies the targeted resolution and local accuracy by an autonomous mobile robot. The proposed framework consists of three steps. Each step is intended to aid in resolving the challenges faced by conventional approaches. In order to ensure the pose estimation is performed with high accuracy, a globally accurate coarse map of the environment is created using a conventional technique such as simultaneous localization and mapping or structure from motion with bundle adjustment. The high scan accuracy is ensured by planning a path for the robot to revisit the environment while maintaining a desired distance to all occupied regions. Since the map is to be created with targeted metrics, an online path replanning and pose refinement technique is proposed to autonomously achieve the metrics without compromising the pose and scan accuracy. The proposed framework was first validated on the ability to address the current challenges associated with accuracy through parametric studies of the proposed steps. The autonomous capability of the proposed framework was been demonstrated successfully in its use for a practical mission.
first_indexed 2024-03-11T04:33:51Z
format Article
id doaj.art-41ff80f0ab6443789c69ba2a9053e0c1
institution Directory Open Access Journal
issn 2218-6581
language English
last_indexed 2024-03-11T04:33:51Z
publishDate 2023-03-01
publisher MDPI AG
record_format Article
series Robotics
spelling doaj.art-41ff80f0ab6443789c69ba2a9053e0c12023-11-17T21:14:11ZengMDPI AGRobotics2218-65812023-03-011223910.3390/robotics12020039A Multistage Framework for Autonomous Robotic Mapping with Targeted MetricsWilliam Smith0Yongming Qin1Siddharth Singh2Hudson Burke3Tomonari Furukawa4Gamini Dissanayake5VICTOR Laboratory, University of Virginia, Charlottesville, VA 22903, USAVICTOR Laboratory, University of Virginia, Charlottesville, VA 22903, USAVICTOR Laboratory, University of Virginia, Charlottesville, VA 22903, USAVICTOR Laboratory, University of Virginia, Charlottesville, VA 22903, USAVICTOR Laboratory, University of Virginia, Charlottesville, VA 22903, USACenter for Autonomous Systems, University of Technology, Sydney, NSW 2007, AustraliaHigh-quality maps are pertinent to performing tasks requiring precision interaction with the environment. Current challenges with creating a high-precision map come from the need for both high pose accuracy and scan accuracy, and the goal of reliable autonomous performance of the task. In this paper, we propose a multistage framework to create a high-precision map of an environment which satisfies the targeted resolution and local accuracy by an autonomous mobile robot. The proposed framework consists of three steps. Each step is intended to aid in resolving the challenges faced by conventional approaches. In order to ensure the pose estimation is performed with high accuracy, a globally accurate coarse map of the environment is created using a conventional technique such as simultaneous localization and mapping or structure from motion with bundle adjustment. The high scan accuracy is ensured by planning a path for the robot to revisit the environment while maintaining a desired distance to all occupied regions. Since the map is to be created with targeted metrics, an online path replanning and pose refinement technique is proposed to autonomously achieve the metrics without compromising the pose and scan accuracy. The proposed framework was first validated on the ability to address the current challenges associated with accuracy through parametric studies of the proposed steps. The autonomous capability of the proposed framework was been demonstrated successfully in its use for a practical mission.https://www.mdpi.com/2218-6581/12/2/39mappingpath planninginspectionmultistageautonomous
spellingShingle William Smith
Yongming Qin
Siddharth Singh
Hudson Burke
Tomonari Furukawa
Gamini Dissanayake
A Multistage Framework for Autonomous Robotic Mapping with Targeted Metrics
Robotics
mapping
path planning
inspection
multistage
autonomous
title A Multistage Framework for Autonomous Robotic Mapping with Targeted Metrics
title_full A Multistage Framework for Autonomous Robotic Mapping with Targeted Metrics
title_fullStr A Multistage Framework for Autonomous Robotic Mapping with Targeted Metrics
title_full_unstemmed A Multistage Framework for Autonomous Robotic Mapping with Targeted Metrics
title_short A Multistage Framework for Autonomous Robotic Mapping with Targeted Metrics
title_sort multistage framework for autonomous robotic mapping with targeted metrics
topic mapping
path planning
inspection
multistage
autonomous
url https://www.mdpi.com/2218-6581/12/2/39
work_keys_str_mv AT williamsmith amultistageframeworkforautonomousroboticmappingwithtargetedmetrics
AT yongmingqin amultistageframeworkforautonomousroboticmappingwithtargetedmetrics
AT siddharthsingh amultistageframeworkforautonomousroboticmappingwithtargetedmetrics
AT hudsonburke amultistageframeworkforautonomousroboticmappingwithtargetedmetrics
AT tomonarifurukawa amultistageframeworkforautonomousroboticmappingwithtargetedmetrics
AT gaminidissanayake amultistageframeworkforautonomousroboticmappingwithtargetedmetrics
AT williamsmith multistageframeworkforautonomousroboticmappingwithtargetedmetrics
AT yongmingqin multistageframeworkforautonomousroboticmappingwithtargetedmetrics
AT siddharthsingh multistageframeworkforautonomousroboticmappingwithtargetedmetrics
AT hudsonburke multistageframeworkforautonomousroboticmappingwithtargetedmetrics
AT tomonarifurukawa multistageframeworkforautonomousroboticmappingwithtargetedmetrics
AT gaminidissanayake multistageframeworkforautonomousroboticmappingwithtargetedmetrics