Multi-Agent Action Graph Based Task Allocation and Path Planning Considering Changes in Environment

Task allocation and path planning considering changes in the mobility of robots environment allows to efficiently execute tasks with smaller travel times. A lunar base construction is one situations which can more accomplish its goal by taking such into account when performing tasks. For construction, we assumed that a robot executes task building road, aisles were unusable before become usable post execution. If are considered advance, plan wait until move executing task. However, previous studies have not changes, resulting inefficient planning. To solve this problem, developed multi-agent action graph consists multiple layers expresses associated execution terms these layers. In graph, formulated as combinatorial optimization problem optimized using mixed-integer programming. Multi-agent graphs proposed formulation enable efficient robots’ advance. Through simulations, confirmed method completed approximately 16.4% earlier than conventional method, while consuming 16.0% less total energy robots.