Task scheduling system for UAV operations in indoor environment

Abstract

The application of unmanned aerial vehicle (UAV) in indoor environment is emerging nowadays due to the advancements in technology. UAV brings more space flexibility in an occupied or hardly accessible indoor environment, e.g. shop floor of manufacturing industry, greenhouse, and nuclear powerplant. UAV helps in creating an autonomous manufacturing system by executing tasks with less human intervention in a time-efficient manner. Consequently, a scheduler is an essential component to be focused on; yet the number of reported studies on UAV scheduling has been minimal. This work proposes a mathematical model of the problem and a heuristic-based methodology to solve it. To suit near real-time operations, a quick response towards uncertain events and a quick creation of new high-quality feasible schedule are needed. Hence, the proposed heuristic is incorporated with particle swarm optimization algorithm to find a near optimal schedule in a short computation time. This proposed methodology is implemented into a scheduler and tested on a few scales of datasets generated based on real flight demonstrations. Performance evaluation of scheduler is discussed in detail, and the best solution obtained from a selected set of parameters is reported.

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

“…Overall, the most common objectives in routing for a set of locations include minimizing operational cost , minimizing fixed costs (mostly the number of required drones ), and minimizing makespan . Several articles consider objectives related to customer service and customer satisfaction, such as expected waiting time of customers for service , share of successfully served customer orders , total customer satisfaction , and resolution of photographed images .…”

Fair Task Allocation When Cost of Task Is Multidimensional

“…The authors of [26] used multi-objective Genetic Algorithms (GA) to solve multi-UAV mission planning. The authors of [27] proposed a methodology with heuristic based on Earliest Available Time algorithm to solve the UAV scheduling problem in an indoor environment incorporated Particle Swarm Optimization (PSO) algorithm, with an objective of minimizing the makespan. However, as the space for the solutions of our problem increases exponentially with the number of tasks and these optimizations usually requires thousands of iterations to converge to the optimal solution when dealing with NP-Hard problems.…”

Spacecraft mission agent for autonomous robust task execution

“…However, in the general field of distributed computing, there are an abundance of papers that discuss scheduling for interdependent tasks with many related works cited in [15]. Similarly, without the restriction of space, there are many papers related to scheduling and autonomy for other platforms such as for Autonomous Underwater Vehicles (AUVs) like in [16] and for Unmanned Aerial Vehicles (UAVs) like in [17]. These systems do not have the same constraints as space systems though and often have a different focus and objective such as for pathplanning and object-detection.…”