SAGL: A New Heuristic for Multi-Robot Routing with Complex Tasks

Heterogeneous Multi-Resource Allocation with Subset Demand Requests

“…The multi-robot task allocation problem is to allocate several homogeneous or heterogeneous robots (resources) to a number of tasks (demands) under system constraints to minimize the makespan (Xu et al (2016); Gombolay et al (2018); Zheng and Koenig (2008); Liu and Kroll (2012)), maximize the utility (Amador Nelke and Zivan (2017)), or minimize the total distance traveled (Kartal et al (2016)). Xu et al (2016); Zheng and Koenig (2008); Liu and Kroll (2012) characterize tasks by spatial constraints whereas Amador Nelke and Zivan (2017); Gombolay et al (2018); Kartal et al (2016) consider both spatial and temporal constraints. Xu et al (2016); Amador Nelke and Zivan (2017); Zheng and Koenig (2008) consider multi-robot tasks, which may require multiple homogeneous (Amador Nelke and Zivan (2017); Xu et al (2016); Zheng and Koenig (2008)) or heterogeneous (Amador Nelke and Zivan (2017)) robots to be completed.…”

“…Xu et al (2016); Zheng and Koenig (2008); Liu and Kroll (2012) characterize tasks by spatial constraints whereas Amador Nelke and Zivan (2017); Gombolay et al (2018); Kartal et al (2016) consider both spatial and temporal constraints. Xu et al (2016); Amador Nelke and Zivan (2017); Zheng and Koenig (2008) consider multi-robot tasks, which may require multiple homogeneous (Amador Nelke and Zivan (2017); Xu et al (2016); Zheng and Koenig (2008)) or heterogeneous (Amador Nelke and Zivan (2017)) robots to be completed. In contrast to our study, in (Amador Nelke and Zivan (2017)) a robot can delay the start or interrupt the service of a task for a penalty, and all tasks are eventually completed, with the goal of maximizing the total utility.…”