Building a Generic Simulation Model for Analyzing the Feasibility of Multi-Robot Task Allocation (MRTA) Problems

Abstract

Multi-Robot Task Allocation (MRTA) will gain much importance by the rise of autonomous vehicles and the Internet of Things (IoT) where several agents coordinate and work for a common goal. Due to their distributed nature, hardware complexity and environmental constraints, constructing and testing multi-robot systems may be expensive, dangerous and time-consuming. MRTA includes sub-problems such as coordination strategy, bid valuation, path planning, terrain complexity, robot design, path optimization, and overall optimization. There is a need for building a generic MRTA model to experiment with these numerous combinations in a controlled and automated fashion. This paper presents the structure of the MRTA generic simulation model which is designed to search for the optimal combination of MRTA taxonomy elements. An MRTA Simulation Tool (MRTASim) is designed to adapt the generic model to specific cases and to run simulations for real-life scenarios. Decision-makers can build their own MRTA models and they can be sure for the feasibility of large distributed and collaborated systems before initiating huge investments.