Recent Results on Information Gathering Path Planning for Autonomous Mobile Robots
| Main Author: | Francesco Amigoni |
|---|---|
| Format: | Proceeding poster Journal |
| Terbitan: |
, 2019
|
| Online Access: |
https://youtu.be/xmgyV2uc2xg |
| ctrlnum |
4794911 |
|---|---|
| fullrecord |
<?xml version="1.0"?>
<dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><creator>Francesco Amigoni</creator><date>2019-10-18</date><description>In the last decades, scientific and technological advances in autonomous mobile robotics have shown that robots can provide a valid alternative to humans in carrying out repetitive, difficult, and hazardous tasks. This is especially true for information gathering tasks, including exploration, search and rescue, monitoring, inspection, and patrolling. This extended abstract overviews some recent results on models and algorithms for planning information gathering paths of single and multiple autonomous mobile robots, focusing on some of the contributions that have been provided by the Artificial Intelligence and Robotics Laboratory (AIRLab) of the Politenico di Milano.</description><description>https://youtu.be/xmgyV2uc2xg</description><identifier>https://zenodo.org/record/4794911</identifier><identifier>10.5281/zenodo.4794911</identifier><identifier>oai:zenodo.org:4794911</identifier><relation>doi:10.5281/zenodo.4794910</relation><relation>url:https://zenodo.org/communities/irim3d-2019</relation><rights>info:eu-repo/semantics/openAccess</rights><rights>https://creativecommons.org/licenses/by/4.0/legalcode</rights><title>Recent Results on Information Gathering Path Planning for Autonomous Mobile Robots</title><type>Journal:Proceeding</type><type>Other:poster</type><recordID>4794911</recordID></dc>
|
| format |
Journal:Proceeding Journal Other:poster Other Journal:Journal |
| author |
Francesco Amigoni |
| title |
Recent Results on Information Gathering Path Planning for Autonomous Mobile Robots |
| publishDate |
2019 |
| url |
https://youtu.be/xmgyV2uc2xg |
| contents |
In the last decades, scientific and technological advances in autonomous mobile robotics have shown that robots can provide a valid alternative to humans in carrying out repetitive, difficult, and hazardous tasks. This is especially true for information gathering tasks, including exploration, search and rescue, monitoring, inspection, and patrolling. This extended abstract overviews some recent results on models and algorithms for planning information gathering paths of single and multiple autonomous mobile robots, focusing on some of the contributions that have been provided by the Artificial Intelligence and Robotics Laboratory (AIRLab) of the Politenico di Milano. |
| id |
IOS16997.4794911 |
| institution |
ZAIN Publications |
| institution_id |
7213 |
| institution_type |
library:special library |
| library |
Cognizance Journal of Multidisciplinary Studies |
| library_id |
5267 |
| collection |
Cognizance Journal of Multidisciplinary Studies |
| repository_id |
16997 |
| subject_area |
Multidisciplinary |
| city |
Stockholm |
| province |
INTERNASIONAL |
| shared_to_ipusnas_str |
1 |
| repoId |
IOS16997 |
| first_indexed |
2022-06-06T05:35:47Z |
| last_indexed |
2022-06-06T05:35:47Z |
| recordtype |
dc |
| _version_ |
1734905738865672192 |
| score |
17.608967 |