Using the PROMETHEE multi-criteria decision making method to define new exploration strategies for rescue robots

The exploration of an unknown environment by a robot system (an individual robot or a team of robots) is a well-studied problem in robotics. This problem has many applications and, among them, the post-disaster search of victims in an urban space. Most of proposed exploration algorithms are based on the use of specific criteria to define the quality of the possible movements. In this paper, we propose an exploration approach based on the combination of several criteria thanks to the PROMETHEE II multi-criteria decision making method. The PROMETHEE II method allows one to establish a complete ranking between possible movements based on outranking relations. Experimental results show that this approach can be used to effectively combine different criteria and outperforms several classic exploration strategies.

[1]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[2]  Reza Baradaran Kazemzadeh,et al.  PROMETHEE: A comprehensive literature review on methodologies and applications , 2010, Eur. J. Oper. Res..

[3]  B. Roy Méthodologie multicritère d'aide à la décision , 1985 .

[4]  Héctor H. González-Baños,et al.  Navigation Strategies for Exploring Indoor Environments , 2002, Int. J. Robotics Res..

[5]  James P. Ignizio,et al.  A Review of Goal Programming: A Tool for Multiobjective Analysis , 1978 .

[6]  Gerhard Wäscher,et al.  A bibliography on outranking approaches (1988-1982) , 1984 .

[7]  Brian Yamauchi,et al.  Frontier-based exploration using multiple robots , 1998, AGENTS '98.

[8]  Wolfram Burgard,et al.  Coordinated multi-robot exploration , 2005, IEEE Transactions on Robotics.

[9]  A. Boucher,et al.  The AROUND project: Adapting robotic disaster response to developing countries , 2009, 2009 IEEE International Workshop on Safety, Security & Rescue Robotics (SSRR 2009).

[10]  Wolfram Burgard,et al.  Exploring Unknown Environments with Mobile Robots using Coverage Maps , 2003, IJCAI.

[11]  Vincenzo Caglioti,et al.  A Mobile Robot Mapping System with an Information-Based Exploration Strategy , 2004, ICINCO.

[12]  R. Benayoun,et al.  Linear programming with multiple objective functions: Step method (stem) , 1971, Math. Program..

[13]  B. Roy THE OUTRANKING APPROACH AND THE FOUNDATIONS OF ELECTRE METHODS , 1991 .

[14]  Matthias Ehrgott,et al.  Multiple criteria decision analysis: state of the art surveys , 2005 .

[15]  Patrick Taillandier,et al.  Using Belief Theory to Diagnose Control Knowledge Quality: Application to Cartographic Generalisation , 2009, 2009 IEEE-RIVF International Conference on Computing and Communication Technologies.

[16]  Michel Grabisch,et al.  A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid , 2010, Ann. Oper. Res..

[17]  Patrick Taillandier,et al.  GAMA: A Simulation Platform That Integrates Geographical Information Data, Agent-Based Modeling and Multi-scale Control , 2010, PRIMA.

[18]  Adel Guitouni,et al.  Automated learning multi-criteria classifiers for FLIR ship imagery classification , 2007, 2007 10th International Conference on Information Fusion.

[19]  Nicola Basilico,et al.  Exploration strategies based on multi-criteria decision making for search and rescue autonomous robots , 2011, AAMAS.

[20]  Alan Pearman,et al.  Model choice in multicriteria decision aid , 1997 .

[21]  BenayounR.,et al.  Linear programming with multiple objective functions , 1971 .

[22]  Nicola Basilico,et al.  Exploration Strategies based on Multi-Criteria Decision Making for an Autonomous Mobile Robot , 2009, ECMR.

[23]  J. Siskos Assessing a set of additive utility functions for multicriteria decision-making , 1982 .

[24]  Arthur M. Geoffrion,et al.  An Interactive Approach for Multi-Criterion Optimization, with an Application to the Operation of an Academic Department , 1972 .