Efficient Object Search Through Probability-Based Viewpoint Selection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00344509" target="_blank" >RIV/68407700:21230/20:00344509 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/20:00344509

Výsledek na webu

<a href="https://doi.org/10.1109/IROS45743.2020.9340989" target="_blank" >https://doi.org/10.1109/IROS45743.2020.9340989</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS45743.2020.9340989" target="_blank" >10.1109/IROS45743.2020.9340989</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Efficient Object Search Through Probability-Based Viewpoint Selection

Popis výsledku v původním jazyce

The ability to search for objects is a precondition for various robotic tasks. In this paper, we address the problem of finding objects in partially known indoor environments. Using the knowledge of the floor plan and the mapped objects, we consider object–object and object–room co-occurrences as prior information for identifying promising locations where an unmapped object can be present. We propose an efficient search strategy that determines the best pose of the robot based on the analysis of the candidate locations. We optimize the probability of finding the target object and the distance travelled through a cost function. To evaluate our method, several experiments in simulated and real-world environments were performed. The results show that the robot successfully finds the target object in the environment while covering only a small portion of the search space. The real-world experiments with the TurtleBot 2 mobile robot validate the proposed approach and demonstrate that the method performs well also in real environments.

Název v anglickém jazyce

Efficient Object Search Through Probability-Based Viewpoint Selection

Popis výsledku anglicky

The ability to search for objects is a precondition for various robotic tasks. In this paper, we address the problem of finding objects in partially known indoor environments. Using the knowledge of the floor plan and the mapped objects, we consider object–object and object–room co-occurrences as prior information for identifying promising locations where an unmapped object can be present. We propose an efficient search strategy that determines the best pose of the robot based on the analysis of the candidate locations. We optimize the probability of finding the target object and the distance travelled through a cost function. To evaluate our method, several experiments in simulated and real-world environments were performed. The results show that the robot successfully finds the target object in the environment while covering only a small portion of the search space. The real-world experiments with the TurtleBot 2 mobile robot validate the proposed approach and demonstrate that the method performs well also in real environments.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

<a href="/cs/project/EF15_003%2F0000470" target="_blank" >EF15_003/0000470: Robotika pro Průmysl 4.0</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems

ISBN

978-1-7281-6212-6

ISSN

2153-0858

e-ISSN

2153-0866

Počet stran výsledku

8

Strana od-do

6172-6179

Název nakladatele

IEEE Robotics and Automation Society

Místo vydání

Piscataway

Místo konání akce

Las Vegas

Datum konání akce

25. 10. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000714033803117