ISSN E 2409-2770
ISSN P 2521-2419

Multi-Robot Exploration in Unstructured and Dynamic Environments



Vol. 7, Issue 03, PP. 189-196, March 2020

DOI

Keywords: Region Assignment, Unknown environment, Un-structured environment, Dynamic environment, Re-planning

Download PDF


This paper deals with exploration by team of multi-robots in unknown, unstructured and dynamic environments at the same time. The goal of the research is to minimize the total exploration time taken by team of robots to complete the mission and to achieve faster re-planning of their planned path in case of sudden changes in the environment as robots move through the environment. The proposed exploration approach is fully distributive in the sense that all robots are assigned separate regions in an unknown environment with each robot exploring its assigned region. As a first step the environment is partitioned into different regions as available number of robots and then each robot in a team is assigned its separate region for exploration. The proposed approach has been tested in different simulation environments with varying number of robots. Comparison with another approach proves the superiority of the approach in terms of reduction of exploration time in unstructured and changing environments.


  1. Saad Javed, , Institute of Mechatronics Engineering, UET Peshawar, Pakistan.
  2. Muhammad Tahir Khan, , Institute of Mechatronics Engineering, UET Peshawar, Pakistan.
  3. Yasim Ahmad, , Department of Mechatronics Engineering, Air University Islamabad, Pakistan.

Saad Javed Muhammad Tahir Khan Yasim Ahmad "Multi-Robot Exploration in Unstructured and Dynamic Environments" International Journal of Engine Vol. 7 Issue 03 PP. 189-196 March 2020 https://doi.org/10.34259/ijew.20.703189196


[1]   C. Stachniss and W. Burgard, “Exploring unknown environments with mobile robots using coverage maps,” IJCAI Int. Jt. Conf. Artif. Intell., pp. 1127–1132, 2003.

[2] L. Bravo, U. Ruiz, R. Murrieta-cid, G. Aguilar, and E. Chavez, “A distributed exploration algorithm for unknown environments with multiple obstacles by multiple robots A distributed exploration algorithm for unknown environments with multiple obstacles by multiple robots,” no. December, 2017.

[3]  K. M. Wurm, C. Stachniss, and W. Burgard, “Coordinated multi- robot exploration using a segmentation of the environment,” in 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, 2008, pp. 1160–1165.

[4]   P. G. C. N. Senarathne and D. Wang, “A two-level approach formulti-robot coordinated exploration of unstructured environments,” Proc. ACM Symp. Appl. Comput., pp. 274–279, 2012.

[5]  F. Abrate, B. Bona, and M. Indri, “Map updating in dynamic environments,” Robot. (ISR), 2010 …, vol. 83, pp. 296–303, 2010.

[6]   C. P. Mcmillen, P. E. Rybski, and M. M. Veloso, “LEVELS OF  MULTI-  ROBOT COORDINATION FOR DYNAMIC ENVIRONMENTS,” pp. 1–12.

[7]    B. Yamauchi, “Yamauchi-frontierExploration98,” no. May, 1998.

[8]    R. Sharma K., D. Honc, F. Dusek, and G. Kumar T., “Frontier Based Multi Robot Area Exploration Using Prioritized Routing,” pp. 25–30, 2016.

[9]  R. Simmons et al., “Coordination for Multi-Robot Exploration and Mapping,” Proc. Natl. Conf. Artif. Intell., pp. 852–858, 2000.

[10]  J. A. Castellanos, J. M. M. Montiel, J. Neira, and J. D. Tardós, “The SPmap: A probabilistic framework for simultaneous localization and map building,” IEEE Trans. Robot. Autom., vol. 15, no. 5, pp. 948–952, 1999.

[11] A. Solanas and M. A. Garcia, “Coordinated multi-robot exploration through unsupervised clustering of unknown space,” pp. 717–721, 2005.

[12]  A. Pal, R. Tiwari, and A. Shukla, “Multi robot exploration using a modified A* algorithm,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 6591 LNAI, no. PART 1, pp. 506–516, 2011.

[13]   A. Pal, R. Tiwari, and A. Shukla, “Multi robot exploration through pruning frontiers,” Adv. Mater. Res., vol. 462, pp. 609–616, 2012.

[14]  B. Yamauchi, “Frontier-based exploration using multiple robots,” no. May, pp. 47–53, 2004.

[15]   R. Zlot, A. Stentz, M. B. Dias, and S. Thayer, “Multi-robot exploration     controlled by a market economy,” pp. 3016–3023, 2003.

[16]  H. Lau, “Behavioural approach for multi-robot exploration,” Australas. Conf. Robot. Autom., pp. 1–7, 2003.

[17] A. Renzaglia and A. Martinelli, “Potential field based approach for   coordinate exploration with a multi-robot team,” 8th IEEE Int. Work. Safety, Secur. Rescue Robot. SSRR-2010, 2010.

[18]   J. De Hoog and S. Cameron, “.”

[19]  R. Arezoumand, S. Mashohor, and M. H. Marhaban, “Finding Objects with Segmentation Strategy based Multi Robot Exploration in Unknown Environment,” Procedia - Soc. Behav. Sci., vol. 97, pp. 580–586, 2013.

[20]   J. J. Lopez-perez, U. H. Hernandez-belmonte, M. A. Contreras-cruz, and V. Ayala-ramirez, “Distributed Multirobot Exploration Based on Scene Partitioning and Frontier Selection,” vol. 2018, 2018.

[21]   H. Liu, H. Wen, and Y. Li, “Path Planning in Changing Environments by Using Optimal Path Segment Search,” pp. 1439–1445, 2009.

[22]   M. L. Tazir, O. Azouaoui, M. Hazerchi, and M. Brahimi, “Mobile Robot Path Planning for Complex Dynamic Environments,” 2015.

[23] A. Vemula, K. Muelling, and J. Oh, “Path Planning in Dynamic Environments with Adaptive Dimensionality.”

[24]  R. S. Society, R. S. Society, and A. Statistics, “Algorithm AS 136 A K-Means Clustering Algorithm,” vol. 28, no. 1, pp. 100–108, 2012.

[25] Harvard University, “The Assignment Problem and the Hungarian Method,” Introd. to Linear Algebr. Multivariable Calc., 2005.

[26]  S. Koenig and M. Likhachev, “D* Lite,” Proc. Natl. Conf. Artif. Intell., pp. 476–483, 2002.