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

Result code in 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>
Result on the web
<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>

Result language
angličtina
Original language name
Multi-Robot Path Planning for Budgeted Active Perception with Self-Organising Maps
Original language description
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.
Czech name
—
Czech description
—

Project
<a href="/en/project/GJ15-09600Y" target="_blank" >GJ15-09600Y: Adaptive Informative Path Planning in Autonomous Data Collection in Dynamic Unstructured Environments</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on
ISBN
978-1-5090-3762-9
ISSN
2153-0866
e-ISSN
—
Number of pages
8
Pages from-to
3164-3171
Publisher name
IEEE
Place of publication
Piscataway
Event location
Daejeon
Event date
Oct 9, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000391921703052

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