An Interactive Multi-Objective Decision-Aiding System for Tactical Mission Planning

The United States and its partners have begun a program to extend human presence in the solar system, beginning with a return to the Moon. The Lunar Reconnaissance Orbiter (LRO) is the first step in this endeavor, an unmanned mission to create the comprehensive atlas of the Moon's features and resources necessary to design and build a lunar outpost. LRO focuses on the selection of safe landing sites, identification of lunar resources, and the study of how the lunar radiation environment will affect humans. In order to achieve its objectives LRO carries a payload comprised of six instruments and one technology demonstration. In addition to its scientific mission LRO will use new technologies, systems and flight operations concepts to reduce risk and increase productivity of future missions. As part of the effort to achieve robust and efficient operations the LRO Mission Operations Team (MOT) will use its Mission Planning System (MPS) to manage the operational activities of the mission during the Lunar Orbit Insertion (LOI) and operational phases of the mission. The MPS, based on GMV’s flexplan tool, will receive activity and slew maneuver requests from multiple science operations centers (SOC), as well as from the spacecraft engineers. flexplan will apply scheduling rules to all the requests received and will generate conflict free command schedules in the form of daily stored command loads for the orbiter and a set of daily pass scripts that help automate nominal real-time operations. The MPS will also track the status of onboard flight software load files in the various onboard memory locations. The LRO mission is using a new Flight Software architecture, the Core Flight Executive (cFE), in which all onboard memory is managed as a file system. The MPS will interact with the ITOS real-time system to receive messages whenever changes are made to the memory content. The MPS will further interact with the real-time system in a closed loop mode to monitor the progress of planned activities. The LRO mission will use this feedback to provide continuous visibility of the status of daily operations to all of its team members via flexplan web-based interface, which includes a timeline of upcoming operations. By using a single MPS system to schedule multiple mission elements and generate automation products, the MOT will be able to reduce the risk of operator errors, while maintaining a high level of mission operations awareness among all mission elements. This in turn, achieves safer and more efficient flight operations at low cost.

: Current mission preparation and analysis methods place an undue burden of effort on conventional and special operations forces to effectively synchronize and execute their increasingly complex operational responsibilities in a rapidly changing global environment. This thesis developed a tool for the United States Special Operations Command (USSOCOM) in support of their Mission Planning, Analysis, Rehearsal, and Execution (MPARE) initiative to allow special operations forces commanders and staffs to conduct mission planning and analysis in a distributed environment, and rapidly produce dynamic synchronization matrices and scheduling products. Operations research methods provide the foundation for the analysis. The system developed in this thesis is called the Special Operations Mission Planning and Analysis Support System (SOMPASS). SOMPASS is simple to learn and operate, provides dynamic changes with little effort, and is universal in application. This system has the capability to execute on any hardware platform, operate across any network connection, and expand easily to support additional users and requirements. This thesis provides not only a demonstration of capabilities through a special operations oriented illustrative scenario, but also a working product that can be adapted for use in mission planning and analysis by all units under USSOCOM.

The KOMPSAT-2 (KOrea Multi-Purpose SATellite-2) was launched in July 28, 2006 and has been normally operated. Mission planning system provides the capability to make conflict-free satellite mission schedule by predicting and analyzing satellite orbital events and users’ imaging requests. The amount of satellite mission planning has been increased due to the growing number of image requests. In order to meet the demands of lots of satellite mission planning activities, all mission plans have to be automatically verified without human intervention. Automation concept is also needed because these planning activities have to be done by the pre-defined timeline. To resolve these problems, MPVS(Mission Planning Verification System) has been developed by mission planning team. The MPVS automatically verifies mission plan with satellite contact schedules, resources and constraints. This paper presents the operational concept of the MPVS which verifies mission plan of the KOMPSAT-2. Also design architecture of the MPVS which is composed of the mission planning verification module, command planning verification module, contact schedule generation module, and database including resources and constraints is presented. This paper shows operation results of the MPVS and validity of the KOMPSAT-2 operation.

Advanced countries around the world are spurring the development of Unmanned Surface Vehicles (USVs) that can operate autonomously at marine environment. The key enabling technology for such USVs is the mission planning system (MPS) that can autonomously navigate through the harsh waters. The MPS not only has the functions for the navigation, but also has the capabilities, such as obstacle avoidance, malfunction corrections, dealing with unexpected events, return home functions, and many other eventualities that cannot be programmed in advance. The autonomy levels are increasingly moving higher and it is foreseeable that the trend will continue in the future. The main purpose of this paper is the analysis of the MPS onboard the USVs, in terms of the categories, functions, and technological details. Also, we analyze the case study of autonomous mission planning control systems in various fields and introduce the features that constitute the critical functionalities of the mission planning systems.

Increased operational constraints on spacecraft and ground station operations have led to stricter ground software management and better performance throughput. For Mission Planning and Scheduling Systems, the ability to process numerous scheduling and planning input requests from multiple systems, applying high-level logistical rules, and providing export capabilities to all external entities, including the spacecraft itself, must be balanced against system performance. The constraint on the processing time of the schedule comes from a mission-defined need-by time, which is driven by execution or contact time. flexplan, an operational Mission Planning and Scheduling (MPS) system, has addressed the balance of performance and system capabilities. flexplan utilizes a combination of a relational database and soft-algorithm scheduling to maximize system performance. This paper demonstrates the method for the design of the internal database processing and maintenance. Performance methodologies and capabilities are presented to demonstrate software strength in two case studies: The Lunar Reconnaissance Orbiter (LRO) low lunar-orbit science mission currently operational and the Ground Network Schedule System (GNSS) multi-mission, multi-stations study of NASA’s infrastructure.

In this paper, a mission planning system is presented that generates mission plans for a group of unmanned aerial vehicles (UAVs) to provide continuous surveillance over an urban area. Given the information of terrain and buildings in the target area, a two-stage approach is employed to solve the problem. In the first stage, a set of camera locations called the vantage set is generated that provides complete coverage of the target area. In the second stage, one or several UAVs are determined to collectively share the vantage set and their individual paths are generated to carry out the continuous surveillance duty. In both stages, evolutionary algorithms (genetic algorithm for vantage set generation and ant colony system for UAV/path planning) are used to search for the optimal solution. During the search, constraints such as the flying capabilities of UAVs and collision avoidance are imposed to guarantee the feasibility of the final result.

The European Space Operations Centre (ESOC) is responsible for operating spacecraft covering a large range of mission types. These range from planetary probes/deep space missions through observatories and science missions to earth observation. All of these different types of missions have the need to plan operations on the spacecraft and, increasingly, of the ground segment. Typically the planning systems used to carry out this process have been implemented on a mission specific basis, at best utilizing some elements from a similar mission type. Reuse across different mission types has typically been almost non-existent. In order to increase synergy in the development of mission planning systems ESOC has started work to define a mission planning framework that can be used to build planning systems for any of the mission types operated. To do this it has been necessary to obtain input from the flight control teams of missions in operation and development. This has proved to be an interesting exercise as one of the main issues has been defining the terminology that was required. Whilst the terminology used amongst missions of the same type is similar it varies significantly between the mission types. This obviously adds considerably to the difficulty in trying to define a common approach to mission planning. To address this issue it was first necessary to define a set of terminology that was clear to all participants and could be used as the basis for defining a common concept. Once this has been done it then proved possible to identify a workflow that was largely applicable to most (although not all) missions. This workflow is as seen by the “planning team” part of a flight control team (FCT); no assumptions have been made as to whether the planning team is solely dedicated to planning activities, only that the planning is carried out as an FCT function.

Trajectory prediction is critical for ensuring the safety, reliability, and scalability of Unmanned Aerial Vehicle (UAV) in urban environments. Despite advances in deep learning, existing methods often struggle with dynamic UAV conditions, such as rapid directional changes and limited forecasting horizons, while lacking comprehensive real-time validation and generalization capabilities. This study addresses these challenges by proposing a gated recurrent unit (GRU)-based deep learning framework optimized through Look_Back and Forward_Length labeling to capture complex temporal patterns. The model demonstrated state-of-the-art performance, surpassing existing unmanned aerial vehicles (UAV) and aircraft trajectory prediction approaches, including FlightBERT++, in terms of both accuracy and robustness. It achieved reliable long-range predictions up to 4 s, and its real-time feasibility was validated due to its efficient resource utilization. The model’s generalization capability was confirmed through evaluations on two independent UAV datasets, where it consistently predicted unseen trajectories with high accuracy. These findings highlight the model’s ability to handle rapid maneuvers, extend prediction horizons, and generalize across platforms. This work establishes a robust trajectory prediction framework with practical applications in collision avoidance, mission planning, and anti-drone systems, paving the way for safer and more scalable UAV operations.

Developing a software system for mission planners at NASA’s Johnson Space Center (JSC) to plan and schedule activities onboard the Space Shuttle or International Space Station (ISS) is a complex task. Due to the scope of the complete user requirements and budget restrictions, a full development of all capabilities was not practical. The planning system had to include not only capabilities for planning the daily activities onboard the spacecraft, but also had to include the capability to upload the plans to the onboard system and to merge plans and activities from planners at other remote planning centers, including Marshall Space Flight Center (MSFC) and International Partners. The Integrated Planning System (IPS) Consolidated Planning System (CPS) was developed in an incremental fashion to continually meet the most immediate needs for the users. CPS has been under development for over 8 years and has been operational at JSC for 5 years, supporting Space Shuttle Program (SSP) and ISS mission planning. The journey to this point of software capabilities has been slow, but steady. The current size of the software application is over 380 K SLOC. Initial development focused on capability for scheduling SSP missions, as this was the most immediate need. Next, the development focused on ISS capability, such as plan upload and advanced long-range planning techniques. Finally, the development focused on including/merging data from MSFC and the International Partners. This paper documents some of the “Lessons Learned” during the development of the CPS. Some examples of these include: • Focusing on current operational needs creates system requirements that may not be applicable in future operations • File exchange mechanism uses a proprietary file format that is not flexible to change • Size and quantity of current planning data seriously hampers performance of the system • Incremental approach to development adds new functionality as peripheral to core functionality The nature of “Lessons Learned” tends to focus our attention on deficiencies in the software. We look at actions or functionality that could have been implemented better or planned better. Focusing on these may give the reader the false impression that the CPS is a short sighted, unusable system. However, the system is stable and quite comprehensive in its capabilities for planning current ISS and SSP operations. The incremental approach allowed the development team to tailor the software to shifting user requirements as planning user operations scenarios and requirements changed. Overall, the CPS is an excellent planning system. This paper is intended to provide some assistance in a “path through the mine field” of software development for planning space mission operations. It is hoped that these “Lessons Learned” can be applied in future space mission planning system projects to avoid some of the limitations of the current system.

Mission planning system is the core part of Earth observation satellites ground management, and it is a complex NP hard problem. This paper summarized the advantages and disadvantages of various mathematical models of the planning system today. And papers also analyzed the adaptability and Optimization result of intelligent algorithms in many different situations. Finally, the article gives the current EOS satellite mission planning system's latest developments and trends in the future.

The Alaska Synthetic Aperture Radar (SAR) Facility Mission Planning Subsystem is an interactive mission planning software system on the VAXStation 2000. This system has the capability to generate satellite ephemerides and mission parameters related to synthetic aperture radar missions. The mission data can be viewed as overlays on the world map in various projections and zooms. The system also provides schedule planning capabilities, using the INGRES DBMS to keep track of the various plans and schedules generated by the mission planner.

The scale of Earth observation satellite system continues to expand and its application is becoming more and more extensive, which puts forward higher requirements for satellite mission planning system. This paper summarizes and analyzes some key issues in the mission planning of earth observation satellites. Firstly, the development status and the trend of earth observation satellites are introduced. Secondly, we summarize and analyze complex requirements of observation decomposition method, the priority of requirements determination method, the model construction and solving methods of single-satellite scheduling, multi-satellite integrated scheduling and multi-satellite dynamic scheduling in the process of requirements Integrated Preprocessing and mission planning. Finally, we discuss the problems that still need to be solved and the direction of research.

The article examines the content and methodological foundations of strategic planning of a modern enterprise, primarily as a basis for determining the plans and objectives of an enterprise, including the volume and structure of the product range, and the resources required for its production and sale. The key differences between strategic and tactical planning are presented. The components of the planning system are considered. A generalized model of planning at an enterprise is presented, as well as a general system of enterprise plans that lie in the field of operational and strategic management and which are advisable to use. One of the manifestations of strategic planning - business planning – is studied, the essence and goals of business planning are considered. The author provides a list of the most well-known and internationally tested international business planning methods. Since strategic planning determines the goal and means of its achievement, it is quite logical to consider the existing classifications of strategic planning stages and determine the most concise and affordable option for entrepreneurship in modern conditions. It is argued that strategic planning is an adaptive process which involves regular development and adjustment of formalized plans with due regard to changes occurring inside and outside the enterprise. Within this process, four main types of management activities can be distinguished: resource allocation; adaptation to the external environment; internal; and organizational strategic foresight. It is noted that administrative tools such as tactics, policies, procedures and rules are used to implement enterprise strategies. The author provides a list of key features of strategic planning, including the need to monitor and coordinate all enterprise operations; defining in the strategies specific measures for the actual implementation of all goals and objectives; thorough and timely identification of threats and adequate response to them; ensuring a close relationship between multi-level strategic, tactical and business plans; etc. which should be considered under martial law.

Designing a Mixed-Initiative Decision-Support System for Multi-UAS Mission Planning

A multi-criteria decision support system for multi-UAV mission planning