A Multi-UAS Trajectory Optimization Methodology for Complex Enclosed Environments Sarah Barlow 1 , Youngjun Choi 2 , Simon Briceno 3 , and Dimitri N. Mavris 4 Abstract—This paper explores a multi-UAV trajectory opti- mization methodology for confined environments. One poten- tial application of this technology is performing warehouse inventory audits; this application is used to evaluate the methodologie’s impact on minimizing total mission times. This paper investigates existing algorithms and improves upon them to better address the constraints of warehouse-like environ- ments. An existing inventory scanning algorithm generates sub- optimal, collision free paths for multi-UAV operations, which has two sequential processes: solving a vehicle routing problem, and determining optimal deployment time without any collision. To improve the sub-optimal results, this paper introduces three possible improvements on the multi-UAV inventory tracking scenario. First, a new algorithm logic which seeks to minimize the total mission time once collision avoidance has been ensured rather than having separate processes. Next, an objective function that seeks to minimize the maximum UAV mission time rather than minimizing the total of all UAV mission times. Last, an operational setup consisting of multiple deployment locations instead of only one. These algorithms are evaluated individually and in combination with one another to assess their impact on the overall mission time using a representative inventory environment. The best combination will be further analyzed through a design of experiments by varying several inputs and examining the resulting fleet size, computation time, and overall mission time. I. INTRODUCTION Over the past few decades, UAVs have had a dramatic increase in popularity. Significant enhancements have been made to UAS technology which enables these vehicles to fly faster, longer, have more stability and control, and even carry payloads [1]. As technology continues to advance and UAVs become more accessible, the feasibility and benefits of the integration of these vehicles will drastically expand, as they will be enabled to support a plethora of new operations. Some of the operations currently being considered and explored are site surveying, terrain mapping, natural disaster monitoring, package delivery, wildlife preservation, search and rescue missions, traffic management, and manufactur- ing/warehouse inventory tracking [2]. Indoor use of UAVs evades the barriers of government/FAA regulations, which *This work was not supported by any organization 1 Sarah Barlow is a Graduate Research with the School of Aerospace En- gineering, Georgia Institute of Technology, sbarlow3@gatech.edu 2 Youngjun Choi is a Research Engineer with the School of Aerospace Engineering, Georgia Institute of Technology, ychoi95@gatech.edu 3 Simon Briceno is a Senior Research Engineer with the School of Aerospace Engineering, Georgia Institute of Technology, briceno@gatech.edu 4 Dimitri N. Mavris is a S.P. Langley Distinguished Regents Professor with the School of Aerospace Engineering, Georgia Institute of Technology, dimitri.mavris@aerospace.gatech.edu allows for more design freedom. Typically, the use cases sur- rounding UAVs occur in outdoor settings, but manufacturing and warehouse environments pose an interesting indoor use case due to their vast sizes. Inside the massive warehouse and manufacturing spaces there exists very complex logistics and operations, where UAVs could prove to be advantageous. Large manufacturing and warehouse environments rou- tinely and frequently perform inventory audits to track the products, supplies, and equipment they have on hand. It is important to keep an accurate count because much of the inventory is expensive or may be needed to fulfill customer orders. The current process of performing one of these audits consists of workers manually scanning each and every item. This proves to be a very time consuming and labor intense practice which is extremely prone to human error due to the constant repetition [3]. Due to the extensive time this process takes, it is impossible to maintain real-time or even remotely close to real-time inventory data. Growing demands to stay competitive, improve customer satisfaction, improve warehouse safety, and increase cost and time savings create a need for more efficient and accurate processes [4]. Some companies with large warehouses, such as Amazon, Walmart, and Ikea, have begun exploring the benefits of incorporating UAS into their business models [4]. UAS platforms have also begun exploring the possibilities of ex- panding and accommodating to these types of environments by packaging together the necessary technologies that a UAV may need to be fit for such a task. Some of these integrated systems include Infinium Scan and EyeSee, which are UAS platforms designed specifically for warehouse environments and inventory tracking [5]. The integration of UAS in these environments could provide substantial labor cost and time savings, while also improving count accuracy with closer to real-time data and fewer missed items. The rising interest in assimilating UAVs in manufacturing and warehouse environ- ments is the motivation to further understand the operations of the two components when coupled together. Overall, there is an extensive problem with current ware- house processes and UAVs are a viable solution. However, with this solution, there is a gap in how to safely and efficiently deploy and operate multiple vehicles at the same time within these complex and large warehouse environments to achieve the maximum benefit from the technology. The operation of UAVs in warehouse environments can be studied with a path planning optimization algorithm. Optimization algorithms consist of three main compo- nents: decision variables, constraints, and objective/cost functions. The three in combination define an algorithm that