Commanding Cooperative UGV-UAV With Nested Vehicle Routing for Emergency Resource Delivery

Abstract

Unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) have been widely used in delivery. In the context of the COVID-2019, in order to control the development of the epidemic, many places have adopted measures to isolate and close the area once a confirmed case is found. While reducing the contact between people, it also blocks the normal driving of vehicles. Only by changing the traditional logistics and distribution methods can customers who have been in a closed and isolated area for a long time be served. Therefore, we use the Cooperative UGV-UAV to achieve it. In this paper, when commanding cooperative UGV and UAV for emergency resource delivery, we mainly focus on two questions: how to accept the operation order (OPORD) from the commander, how to generate a nested vehicle routing planning. We first employ one intelligent task understanding module to drive the intelligent unmanned vehicles to accept and process the C-BML (Coalition Battle Management Language) formatted OPORD with 5W (what, who, where, why, when) elements. Then, we slove the nested vehicle routing planning problem as a mixed integer linear program (MILP) with the outputs of what is the UGV route, what is the UGV sortie, and how to control the customers' distribution between the UGV and the UAV. Experimental results of random instances and case study show that using the iterative improvement algorithm increase the speed rate of solving more than 10%.

Vehicle Routing Optimization for Pandemic Containment: A Systematic Review on Applications and Solution Approaches

“…Due to the critical nature of sustainability in the post-pandemic era, future studies should emphasize the importance of emission reduction or risk minimization. Shen (2009b) [67] Ceselli (2014) [68] Clarke (2017) [93] Akwafuo (2020) [96] EL Midaoui (2020) [94] Gao (2020) [104] Muslu (2020) [103] Pacheco (2020) [91] Calvet (2020) [92] Gai (2021) [72] Gamchi (2021) [80] Huilin (2021) [52] Long (2021) [79] Table 14. Cont.…”

“…This finding makes sense, given the importance of using pharmaceutical interventions to control the pandemic. In addition, nine articles examined e-commerce logistics services, such as fresh food shipping [69,89,102] and parcel delivery [85,86,90,100,103,106], while four papers referred to on-demand transportation services [70,104,108,109], the use of which has been accelerated by the onset of COVID-19 in urban areas [92]. Among the rest of the articles in this area, one focused on oil distribution and one focused on ready meal delivery in hotels.…”

“…Response time was the factor used most often in the social dimension. The minimization of total time in the route was used in many articles [51,89,98,104,106,107]. In order to optimize the bottleneck route, Pacheco and Laguna [91] proposed an alternative objective function, aiming to minimize the longest route time and ignore all shorter routes.…”

“…Among these, home delivery [69,85,89,108] is a critical consideration in the case of lockdown, where goods are distributed to the designated location and customers pick them up themselves [52,69,108]. In addition, self-driving delivery robots have been used to avoid person-to-person contact [87,104,106,107]. In this strategy, having the optimal number of robots is crucial and this number should be determined by analyzing the relative costs and benefits [87].…”

“…In this strategy, having the optimal number of robots is crucial and this number should be determined by analyzing the relative costs and benefits [87]. Furthermore, in order to accelerate the response to the pandemic, traffic conditions in the delivery path must be taken into account [90,109], while cooperative unmanned ground and aerial vehicles [104], electricity-assisted bicycles [100], and joint distribution modes [89] have also been recommended.…”