Multi-Robot Path Planning for Budgeted Active Perception with Self-Organising Maps

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00307176" target="_blank" >RIV/68407700:21230/16:00307176 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/document/7759489/" target="_blank" >http://ieeexplore.ieee.org/document/7759489/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS.2016.7759489" target="_blank" >10.1109/IROS.2016.7759489</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multi-Robot Path Planning for Budgeted Active Perception with Self-Organising Maps

Popis výsledku v původním jazyce

We propose a self-organising map (SOM) algorithm as a solution to a new multi-goal path planning problem for active perception and data collection tasks. We optimise paths for a multi-robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visiting associated viewpoint regions defined by a sensor model. The key problem characteristics are that the viewpoint regions are overlapping polygonal continuous regions, each node has an observation reward, and the robots are constrained by travel budgets. The SOM algorithm jointly selects and allocates nodes to the robots and finds favourable sequences of sensing locations. The algorithm has polynomial-bounded runtime independent of the number of robots. We demonstrate feasibility for the active perception task of observing a set of 3D objects. The viewpoint regions consider sensing ranges and self-occlusions, and the rewards are measured as discriminability in the ensemble of shape functions feature space. Simulations were performed using a 3D point cloud dataset from a real robot in a large outdoor environment. Our results show the proposed methods enable multi-robot planning for budgeted active perception tasks with continuous sets of candidate viewpoints and long planning horizons.

Název v anglickém jazyce

Multi-Robot Path Planning for Budgeted Active Perception with Self-Organising Maps

Popis výsledku anglicky

We propose a self-organising map (SOM) algorithm as a solution to a new multi-goal path planning problem for active perception and data collection tasks. We optimise paths for a multi-robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visiting associated viewpoint regions defined by a sensor model. The key problem characteristics are that the viewpoint regions are overlapping polygonal continuous regions, each node has an observation reward, and the robots are constrained by travel budgets. The SOM algorithm jointly selects and allocates nodes to the robots and finds favourable sequences of sensing locations. The algorithm has polynomial-bounded runtime independent of the number of robots. We demonstrate feasibility for the active perception task of observing a set of 3D objects. The viewpoint regions consider sensing ranges and self-occlusions, and the rewards are measured as discriminability in the ensemble of shape functions feature space. Simulations were performed using a 3D point cloud dataset from a real robot in a large outdoor environment. Our results show the proposed methods enable multi-robot planning for budgeted active perception tasks with continuous sets of candidate viewpoints and long planning horizons.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

<a href="/cs/project/GJ15-09600Y" target="_blank" >GJ15-09600Y: Adaptivní plánování v úlohách autonomního sběru dat v nestrukturovaném prostředí</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on

ISBN

978-1-5090-3762-9

ISSN

2153-0866

e-ISSN

—

Počet stran výsledku

8

Strana od-do

3164-3171

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Daejeon

Datum konání akce

9. 10. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000391921703052