Event- and time-triggered dynamic task assignments for multiple vehicles

Abstract

We study the dynamic task assignment problem in which multiple dispersed vehicles are employed to visit a set of targets. Some targets' locations are initially known and the others are dynamically randomly generated during a finite time horizon. The objective is to visit all the target locations while trying to minimize the vehicles' total travel time. Based on existing algorithms used to deal with static multi-vehicle task assignment, two types of dynamic task assignments, namely event-triggered and time-triggered, are studied to investigate what the appropriate time instants should be to change in real time the assignment of the target locations in response to the newly generated target locations. Furthermore, for both the eventand time-triggered assignments, we propose several algorithms to investigate how to distribute the newly generated target locations to the vehicles. Extensive numerical simulations are carried out which show better performance of the event-triggered task assignment al-

Multi-robot task assignment for serving people quarantined in multiple hotels during COVID-19 pandemic

“…The task assignment problem for a team of vehicles to visit a set of target locations while trying to minimize the robots' total travel time (10,11) or distance (12,13) is a variant of the vehicle routing problem (VRP) (14). For the VRP, a fleet of vehicles with limited capacity must deliver goods from one or more depots to a group of customers, which is an NP-hard problem (14).…”

“…However, in (10) and (12), the robots' number is equal to the targets' number, where a robot stops moving upon reaching its assigned target location. In (11), several dynamic task assignment algorithms were proposed for multiple vehicles to visit a group of target locations, where some target locations are dynamically generated during the vehicles' movement. Integrated with Dubins car model, a genetic algorithm was designed for multi-UAV task assignment respecting the vehicles' limited turning radius (24).…”

Integrated Task Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery

“…The task assignment aspect of the studied problem is related to multi-robot task allocation problems, which have been widely studied [2], [11]. Most closely related are the VRP [12] and its variants [13], all of which are NP-hard problems.…”

“…Constraint (2) requires that the same robot drops off the task picked up by it; (3) denotes that a task will be transported by a robot if the robot picks up the task; (4) implies that each task is transported by exactly one robot; (5) and ( 6) require that vehicle k will visit all the locations, planned to be visited, at certain time instants; (7) guarantees that the earliest time for the robots to pickup every task is the time when the task is released; (8) ensures that there is no shorter time for each robot to move between two arbitrary locations i and j compared with t(i, j); (9) guarantees that the robots' capacity constraint is always satisfied; (10) and (11) require that there is no collision between any two robots.…”

Efficient Heuristic Algorithms for Single-Vehicle Task Planning With Precedence Constraints

“…As a follow up, a co-evolutionary multipopulation genetic algorithm was proposed for multiple vehicles to deliver products to a set of target locations in a time-varying drift field [31], and an auction-based algorithm was designed for task assignment of multiple vehicles in a drift field with obstacles [32]. In [33], we investigated the dynamic task assignment for multiple vehicles to visit a set of target locations where some target locations are initially known and the other target locations are dynamically generated during the vehicles' movement. In addition, we have investigated the task assignment for heterogeneous vehicles with precedence constraints [34].…”