MRPPSim: A Multi-Robot Path Planning Simulation

Multi-robot path planning problem is an interesting problem of research having great potential for several optimization problems in the world. In multi-robot path planning problem domain (MRPP), robots must move from their start locations to their goal locations avoiding collisions with each other. MRPP is a relevant problem in several domains, including; automatic packages inside a warehouse, automated guided vehicles, planetary exploration, robotics mining, and video games. This work introduces MRPPSim; a new modeling, evaluation and simulation tool for multi-robot path planning algorithms and its applications. In doing so, it handles all the aspects related to the multi-robot path planning algorithms. Through its working, MRPPSim unifies the representation for the input. This algorithm provides researchers with a set of evaluation models with each of them serving a set of objectives. It provides a comprehensive method to evaluate and compare the algorithm’s performance to the ones that solve public benchmark problems inas shown in literature. The work presented in this paper also provides a complete tool to reformat and control user input, critical small benchmark, biconnected, random and grid problems. Once all of this is performed, it calculates the common performance measurements of multi-robot path planning algorithms in a unified way. The work presented in this paper animates the results so the researchers can follow their algorithms’ executions. In addition, MRPPSim is designed as set of models, each is dedicated to a specific function, this allows new algorithm, evaluation model, or performance measurements to be easily plugged into the simulator.

@article{Alotaibi2016,
  title     = {MRPPSim: A Multi-Robot Path Planning Simulation},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {8},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Ebtehal Turki Saho Alotaibi and Hisham Al-Rawi},
  doi       = {10.14569/IJACSA.2016.070821},
  url       = {https://doi.org/10.14569/IJACSA.2016.070821}
}