Abstract
This work presents a framework for multi-robot tour guidance in a partially known environment with uncertainty, such as a museum. In the proposed centralized multi-robot planner, a simultaneous matching and routing problem (SMRP) is formulated to match the humans with robot guides according to their selected places of interest (POIs) and generate the routes and schedules for the robots according to uncertain spatial and time estimation. A large neighborhood search algorithm is developed to efficiently find sub-optimal low-cost solutions for the SMRP. The scalability and optimality of the multi-robot planner are evaluated computationally under different numbers of humans, robots, and POIs. The largest case tested involves 50 robots, 250 humans, and 50 POIs. Then, a photo-realistic multi-robot simulation platform was developed based on Habitat-AI to verify the tour guiding performance in an uncertain indoor environment. Results demonstrate that the proposed centralized tour planner is scalable, makes a smooth tradeoff in the plans under different environmental constraints, and can lead to robust performance with inaccurate uncertainty estimations (within a certain margin).
References
1.
Satake
, S.
, Kanda
, T.
, Glas
, D. F.
, Imai
, M.
, Ishiguro
, H.
, and Hagita
, N.
, 2009
, “How to Approach Humans? Strategies for Social Robots to Initiate Interaction
,” Proceedings of the ACM/IEEE International Conference Human–Robot Interaction
, San Diego, CA
, IEEE, pp. 109
–116
.2.
Shiomi
, M.
, Kanda
, T.
, Glas
, D. F.
, Satake
, S.
, Ishiguro
, H.
, and Hagita
, N.
, 2009
, “Field Trial of Networked Social Robots in a Shopping Mall
,” Proceedings of the IEEE/RSJ International Conference Intelligent and Robotic Systems
, St. Louis, MO
, pp. 2846
–2853
.3.
Doering
, M.
, Kanda
, T.
, and Ishiguro
, H.
, 2019
, “Neural-Network-Based Memory for a Social Robot: Learning a Memory Model of Human Behavior From Data
,” ACM Transactions on Human-Robot Interaction (THRI)
, 8
(4
), pp. 1
–27
.4.
Kirby
, R.
, Forlizzi
, J.
, and Simmons
, R.
, 2010
, “Affective Social Robots
,” Robot. Auton. Syst.
, 58
(3
), pp. 322
–332
. 5.
Burgard
, W.
, Cremers
, A. B.
, Fox
, D.
, Hähnel
, D.
, Lakemeyer
, G.
, Schulz
, D.
, Steiner
, W.
, and Thrun
, S.
, 1998
, “The Interactive Museum Tour-Guide Robot
,” AAAI/IAAI, Madison, WI, pp. 11
–18
.6.
Burgard
, W.
, Cremers
, A. B.
, Fox
, D.
, Hähnel
, D.
, Lakemeyer
, G.
, Schulz
, D.
, Steiner
, W.
, and Thrun
, S.
, 1999
, “The Museum Tour-Guide Robot RHINO,” Autonome Mobile Systeme 1998
, Springer
, Berlin, Germany
, pp. 245
–254
.7.
De Carolis
, B.
, Palestra
, G.
, Della Penna
, C.
, Cianciotta
, M.
, and Cervelione
, A.
, 2019
, “Social Robots Supporting the Inclusion of Unaccompanied Migrant Children: Teaching the Meaning of Culture-Related Gestures
,” J. e-Learn. Knowledge Soc.
, 15
(2
), pp. 43
–57
.8.
Kurata
, Y.
, 2010
, “Interactive Assistance for Tour Planning
.” Spatial Cognition VII
, C.
Hölscher
, T. F.
Shipley
, M. Olivetti
Belardinelli
, J. A.
Bateman
, and N. S.
Newcombe
, eds., Springer Berlin Heidelberg
, pp. 289
–302
.9.
Bennewitz
, M.
, Faber
, F.
, Joho
, D.
, Schreiber
, M.
, and Behnke
, S.
, 2005
, “Towards A Humanoid Museum Guide Robot that Interacts with Multiple Persons
,” Proceedings of the IEEE-RAS International Conference on Humanoid Robots
, Tsukuba, Japan
, IEEE
, pp. 418
–423
.10.
Ford
, L. R.
, and Fulkerson
, D. R.
, 2015
, Flows in Networks
, Princeton University Press
, Princeton, NJ
.11.
Cheng
, Y.-Q.
, Wu
, V.
, Collins
, R.
, Hanson
, A. R.
, and Riseman
, E. M.
, 1996
, “Maximum-Weight Bipartite Matching Technique and Its Application in Image Feature Matching
,” Visual Communications and Image Processing
, Orlando, FL
, Vol. 2727
, International Society for Optics and Photonics
, pp. 453
–462
.12.
Carion
, N.
, Massa
, F.
, Synnaeve
, G.
, Usunier
, N.
, Kirillov
, A.
, and Zagoruyko
, S.
, 2020
, “End-to-End Object Detection with Transformers
,” Proceedings of the European Conference on Computer Vision
, Glasgow, UK
, pp. 213
–229
.13.
Aggarwal
, G.
, Goel
, G.
, Karande
, C.
, and Mehta
, A.
, 2011
, “Online Vertex-Weighted Bipartite Matching and Single-Bid Budgeted Allocations
,” Proceedings of the ACM-SIAM Symposium on Discrete Algorithm
, San Francisco, CA
, SIAM
, pp. 1253
–1264
.14.
Dutta
, A.
, and Asaithambi
, A.
, 2019
, “One-to-Many Bipartite Matching Based Coalition Formation for Multi-Robot Task Allocation
,” Proceedings of the IEEE International Conference on Robots and Automation
, Montreal, Canada
, IEEE
, pp. 2181
–2187
.15.
Mendoza
, J. E.
, and Villegas
, J. G.
, 2013
, “A Multi-Space Sampling Heuristic for the Vehicle Routing Problem with Stochastic Demands
,” Optim. Lett.
, 7
(7
), pp. 1503
–1516
. 16.
Secomandi
, N.
, and Margot
, F.
, 2009
, “Reoptimization Approaches for the Vehicle-Routing Problem With Stochastic Demands
,” Oper. Res.
, 57
(1
), pp. 214
–230
. 17.
Marinakis
, Y.
, Iordanidou
, G.-R.
, and Marinaki
, M.
, 2013
, “Particle Swarm Optimization for the Vehicle Routing Problem With Stochastic Demands
,” Applied Soft Computing
, 13
(4
), pp. 1693
–1704
. 18.
Fu
, B.
, Smith
, W.
, Rizzo
, D.
, Castanier
, M.
, Ghaffari
, M.
, and Barton
, K.
, 2021
, “Robust Task Scheduling for Heterogeneous Robot Teams Under Capability Uncertainty.” arXiv preprint arXiv:2106.12111.19.
Sundar
, K.
, Venkatachalam
, S.
, and Manyam
, S. G.
, 2017
, “Path Planning for Multiple Heterogeneous Unmanned Vehicles with Uncertain Service Times
,” Proceedings of the International Conference on Unmanned Aircraft Systems
, Miami, FL
, IEEE
, pp. 480
–487
.20.
Chen
, L.
, Hà
, M. H.
, Langevin
, A.
, and Gendreau
, M.
, 2014
, “Optimizing Road Network Daily Maintenance Operations with Stochastic Service and Travel Times
,” Transp. Res. Part E: Logistics and Transportation Review
, 64
, pp. 88
–102
. 21.
Li
, X.
, Tian
, P.
, and Leung
, S. C.
, 2010
, “Vehicle Routing Problems With Time Windows and Stochastic Travel and Service Times: Models and Algorithm
,” Int. J. Prod. Econ.
, 125
(1
), pp. 137
–145
. 22.
Gómez
, A.
, Mariño
, R.
, Akhavan-Tabatabaei
, R.
, Medaglia
, A. L.
, and Mendoza
, J. E.
, 2016
, “On Modeling Stochastic Travel and Service Times in Vehicle Routing
,” Transp. Sci.
, 50
(2
), pp. 627
–641
. 23.
Venkatachalam
, S.
, Bansal
, M.
, Smereka
, J. M.
, and Lee
, J.
, 2019
, “Two-Stage Stochastic Programming Approach for Path Planning Problems Under Travel Time and Availability Uncertainties
”. arXiv preprint arXiv:1910.04251.24.
Venkatachalam
, S.
, Sundar
, K.
, and Rathinam
, S.
, 2018
, “A Two-Stage Approach for Routing Multiple Unmanned Aerial Vehicles With Stochastic Fuel Consumption
,” Sensors
, 18
(11
), p. 3756
. 25.
Fu
, B.
, Smith
, W.
, Rizzo
, D.
, Castanier
, M.
, and Barton
, K.
, 2020
, “Heterogeneous Vehicle Routing and Teaming with Gaussian Distributed Energy Uncertainty
,” Proceedings of the IEEE/RSJ International Conference Intelligent Robots and Systems
, Las Vegas, NV
, IEEE
, pp. 4315
–4322
.26.
Toth
, P.
, and Vigo
, D.
, 2002
, The Vehicle Routing Problem
, SIAM
, Philadelphia, PA
.27.
Schreieck
, M.
, Safetli
, H.
, Siddiqui
, S. A.
, Pflügler
, C.
, Wiesche
, M.
, and Krcmar
, H.
, 2016
, “A Matching Algorithm for Dynamic Ridesharing
,” Transp. Res. Procedia
, 19
, pp. 272
–285
. 28.
Aydin
, O. F.
, Gokasar
, I.
, and Kalan
, O.
, 2020
, “Matching Algorithm for Improving Ride-Sharing by Incorporating Route Splits and Social Factors
,” PLoS. One.
, 15
(3
), p. e0229674
. 29.
Sitek
, P.
, and Wikarek
, J.
, 2019
, “Capacitated Vehicle Routing Problem With Pick-Up and Alternative Delivery (cvrppad): Model and Implementation Using Hybrid Approach
,” Annals of Operations Research
, 273
(1
), pp. 257
–277
. 30.
He
, L.
, Liu
, X.
, Laporte
, G.
, Chen
, Y.
, and Chen
, Y.
, 2018
, “An Improved Adaptive Large Neighborhood Search Algorithm for Multiple Agile Satellites Scheduling
,” Computers & Operations Research
, 100
, pp. 12
–25
. 31.
Alinaghian
, M.
, and Shokouhi
, N.
, 2018
, “Multi-Depot Multi-Compartment Vehicle Routing Problem, Solved by a Hybrid Adaptive Large Neighborhood Search
,” Omega
, 76
, pp. 85
–99
. 32.
Deng
, M.
, Fu
, B.
, and Menassa
, C. C.
, 2021
, “Room Match: Achieving Thermal Comfort Through Smart Space Allocation And Environmental Control In Buildings
,” Proceedings of the 2021 Winter Simulation Conference
, Phoenix, AZ
.33.
Heller
, I.
, and Tompkins
, C. B.
, 1956
, “An Extension of a Theorem of Dantzig’s
,” Linear Inequalities and Related Systems
, 38
, pp. 247
–254
.34.
Quigley
, M.
, Conley
, K.
, Gerkey
, B.
, Faust
, J.
, Foote
, T.
, Leibs
, J.
, Wheeler
, R.
, and Ng
, A. Y.
, 2009
, “Ros: An Open-Source Robot Operating System
,” ICRA Workshop on Open Source Software
, Kobe, Japan
, IEEE, p. 5
.35.
Savva
, M.
, Kadian
, A.
, Maksymets
, O.
, Zhao
, Y.
, Wijmans
, E.
, Jain
, B.
, Straub
, J.
, Liu
, J.
, Koltun
, V.
, Malik
, J.
, Parikh
, D.
, and Batra
, D.
, 2019
, “Habitat: A Platform for Embodied AI Research
,” Proceedings of the IEEE International Conference on Computer Vision
, Seoul, South Korea
, IEEE, pp. 9339
–9347
.36.
Chang
, A.
, Dai
, A.
, Funkhouser
, T.
, Halber
, M.
, Niessner
, M.
, Savva
, M.
, Song
, S.
, Zeng
, A.
, and Zhang
, Y.
, 2017
, “Matterport3d: Learning from RGB-D Data in Indoor Environments
.” arXiv preprint arXiv:1709.06158.37.
Kadian
, A.
, Truong
, J.
, Gokaslan
, A.
, Clegg
, A.
, Wijmans
, E.
, Lee
, S.
, Savva
, M.
, Chernova
, S.
, and Batra
, D.
, 2020
, “Sim2real Predictivity: Does Evaluation in Simulation Predict Real-world Performance?
” IEEE Robotics and Automation Letters
, 5
(4
), pp. 6670
–6677
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