A Unified Framework for Reliable Multi-Drone Tasking in Emergency Response Missions

Abstract

In this paper a unified framework is presented for coordinated multi-drone tasking in emergency response missions. As elaborated in this work, response missions can be broken into a number of distinct tasks that can be allocated among the available drone agents to expedite the response operations. The proposed framework enables the development and execution of algorithms that jointly schedule and route drone agents across the field to complete their tasks and successfully address the mission goals considering the agent limitations. The key design challenges of implementing the proposed framework are discussed. Finally, initial simulation and experimental results are presented providing evidence of the real life applicability and reliability of the proposed framework.

Towards a Social-media Driven Multi-Drone Tasking platform

“…The Social-media driven multi-drone tasking (SM+MDT) algorithm proposed in this paper, extends the multi-drone tasking algorithm presented in [10] by leveraging socialmedia to define and prioritise tasks. In particular, SM+MDT considers: a) the urgency of each of the tasks, b) demand of each of the tasks, and c) the capacity (in terms of flight time) of each UAV to complete that task.…”

“…to solve this problem we use Contraint Programming (CP) and in particular we used the library offered by the Operation Research tools (OR-tools) algorithmic toolkit [45]. As a strategy for fiding solutions we use the Path Cheapest arc; that is a greedy algorithm that starts from the source node and connects it to the node with the cheapest route segment, proved effective in previous work [10]. The generated route is further extended by iterating on the last node added to the route.…”

“…The first baseline used is the multi-drone tasking algorithm, which this work aims to optimise. The algorithm [10] takes into account the availability and capacity of the UAVs, their distances from the identified locations and allocates tasks and guide the drones to the desired locations. The locations are evenly distributed in the area of focused and are calculated based on the Field-Of-View of the drones.…”

“…The proposed framework extends our existing framework (detailed in [10] and [11]) to integrate data provided in social-media platforms regarding relevant events and aggregates processed information to conclude on specific tasks. Using these tasks, the proposed framework employs a robust (re)tasking algorithm taking into account the physical limitations of the available drone swarm (including availability and capacity of the UAVs), their distances from the identified locations and their battery availability to guide the drones over the desired locations.…”

SWIFTERS: A Multi-UAV Platform for Disaster Management

“…Collaborative searching enables the utilisation of multiple UAVs to scan an area. The background algorithm, described in detail in [22] takes into account the battery of the UAVs and their estimated maximum flight time to produce paths for each of the selected UAVs in a variation of the Vehicle Routing Problem. The Task manager enables the introduction of more tasks that can extend the useability and enhance the purpose of the SWIFTERS platform.…”