Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

103
The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
103
Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

165
Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
165

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Deep-Learning-Based Context-Aware Multi-Level Information Fusion Systems for Indoor Mobile Robots Safe Navigation.

Sensors (Basel, Switzerland)·2023
Same author

Patient-Specific Finite Element Modeling of the Whole Lumbar Spine Using Clinical Routine Multi-Detector Computed Tomography (MDCT) Data-A Pilot Study.

Biomedicines·2022
Same author

Toward a Comprehensive Domestic Dirt Dataset Curation for Cleaning Auditing Applications.

Sensors (Basel, Switzerland)·2022
Same author

Object-of-Interest Perception in a Reconfigurable Rolling-Crawling Robot.

Sensors (Basel, Switzerland)·2022
Same author

AI-Enabled Mosquito Surveillance and Population Mapping Using Dragonfly Robot.

Sensors (Basel, Switzerland)·2022
Same author

AI-Enabled Predictive Maintenance Framework for Autonomous Mobile Cleaning Robots.

Sensors (Basel, Switzerland)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Sep 3, 2025

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.7K

A Novel Path Planning Strategy for a Cleaning Audit Robot Using Geometrical Features and Swarm Algorithms.

Thejus Pathmakumar1, M A Viraj J Muthugala1, S M Bhagya P Samarakoon1

  • 1Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore.

Sensors (Basel, Switzerland)
|July 27, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel robot-aided cleaning auditing strategy using geometric feature extraction and swarm algorithms to efficiently gather dirt samples. The ant colony optimization algorithm proved optimal for path planning, reducing travel distance and energy consumption.

Keywords:
audit robotcleaning auditinggeometrical featureswarm algorithms

More Related Videos

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.8K
Manufacturing, Control, and Performance Evaluation of a Gecko-Inspired Soft Robot
07:40

Manufacturing, Control, and Performance Evaluation of a Gecko-Inspired Soft Robot

Published on: June 10, 2020

14.7K

Related Experiment Videos

Last Updated: Sep 3, 2025

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.7K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.8K
Manufacturing, Control, and Performance Evaluation of a Gecko-Inspired Soft Robot
07:40

Manufacturing, Control, and Performance Evaluation of a Gecko-Inspired Soft Robot

Published on: June 10, 2020

14.7K

Area of Science:

  • Robotics
  • Environmental Science
  • Computer Science

Background:

  • Robot-aided cleaning auditing requires efficient dirt sample collection for accurate cleanliness assessment.
  • Traditional coverage planning is unsuitable for selective dirt sample gathering.
  • A path planning approach focusing on high-likelihood dirt accumulation areas is more feasible.

Purpose of the Study:

  • To develop a novel dirt sample gathering strategy for cleaning auditing robots.
  • To combine geometric feature extraction with swarm algorithms for optimal path planning.
  • To establish a foundational approach for robot-aided cleaning auditing.

Main Methods:

  • Utilized geometrical feature extraction to identify potential dirt accumulation locations.
  • Integrated swarm algorithms, specifically ant colony optimization, for path planning.
  • Validated the approach through systematic experiment trials and real-world robot deployment.

Main Results:

  • Geometrical feature extraction effectively identified dirt-accumulated locations.
  • Ant colony optimization generated an efficient cleaning auditing path.
  • The proposed method demonstrated reduced travel distance, exploration time, and energy usage.

Conclusions:

  • The combined approach of geometric feature extraction and swarm algorithms provides an efficient and optimal path for cleaning auditing robots.
  • This strategy is foundational for robot-aided cleaning auditing, addressing the challenge of selective dirt sample collection.
  • The ant colony optimization algorithm is highly effective in minimizing operational costs for cleaning auditing robots.