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Optimizing parallel task execution for Multi-Agent Mission Planning

IEEE ACCESS 2023年 11卷 24367-24381页

作者： Miloradovic, Branko Curuklu, Baran Ekstrom, Mikael Papadopoulos, Alessandro Vittorio Malardalen Univ Div Intelligent Future Technol S-72220 Vasteras Sweden

Multi-agent systems have received a tremendous amount of attention in many areas of research and industry, especially in robotics and computer science. With the increased number of agents in missions, the problem of allocation of tasks to agents arose, and it is one of the most fundamental classes of problems in robotics, formally known as the Multi-Robot task Allocation (MRTA) problem. MRTA encapsulates numerous problem dimensions, and it aims at providing formulations and solutions to various problem configurations, i.e., complex multi-agent missions. One dimension of the MRTA problem has not caught much of the research attention. In particular, problem configurations including Multi-task (MT) robots have been neglected. However, the increase in computational power, in robotic systems, has allowed the utilization of parallel task execution. This in turn had the benefit of allowing the creation of more complex robotic missions;however, it came at the cost of increased problem complexity. Our contribution to the aforementioned domain can be grouped into three categories. First, we model the problem using two different approaches, Integer Linear Programming and Constraint Programming. With these models, we aim at filling the gap in the literature related to the formal definition of MT robot problem configuration. Second, we introduce the distinction between physical and virtual tasks and their mutual relationship in terms of parallel task execution. This distinction allows the modeling of a wider range of missions while exploiting possible parallel task execution. Finally, we provide a comprehensive performance analysis of both models, by implementing and validating them in CPLEX and CP Optimizer on the set of problems. Each problem consists of the same set of test instances gradually increasing in complexity, while the percentage of virtual tasks in each problem is different. The analysis of the results includes exploration of the scalability of both models and solv

关键词： task analysis Robots Planning Taxonomy Resource management Complexity theory Analytical models Multi-agent mission planning multi-robot task allocation parallel task execution integer linear programming constraint programming

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Exploiting parallelism in Multi-task Robot Allocation Problems

Exploiting Parallelism in Multi-Task Robot Allocation Proble...

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Miloradovic, Branko Curuklu, Baran Ekstrom, Mikael Papadopoulos, Alessandro, V Malardalen Univ Vasteras Sweden

ISBN: (纸本)9781665431989

Multi-Agent Systems (MASs) have been widely adopted in robotics, as a means to solve complex missions by subdividing them into smaller tasks. In such a context, Multi-Robot task Allocation (MRTA) has been a relevant research area, with the main aim of providing formulations and solutions to different mission configurations, in order to optimize the planning and the execution of complex missions utilizing multiple robots. In recent years, robotic systems have become more powerful thanks to the adoption of novel computing platforms, enabling an increased level of parallelism, in terms of sensing, actuation, and computation. As a result, more complex missions can be achieved, at the cost of an increased complexity for the optimization of the mission planning. In this paper, we first introduce the distinction between physical and virtual tasks of the robots, and their relation in terms of parallel execution. Therefore, we propose a mathematical formalization of the mission planning problem for Multi-task (MT) robots, in the presence of tasks that require only a Single-Robot (SR) to complete, and in the presence of Time-Extended Assignments (TAs). The problem is modeled with a Mixed-Integer Linear Programming (MILP) formulation, with the objective of minimizing the total makespan of the mission, exploiting the potential (physical and virtual) parallelism of the robots. The model is validated over some representative scenarios, and their respective solutions are obtained with the CPLEX optimization tool, showing the generality of the proposed formulation.

关键词： Multi-Robot task Allocation parallel task execution Mixed-Integer Linear Programming

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