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Colombia has embarked on its journey into the space era through the FACSAT program, led by the Colombian Aerospace Force, aiming to deploy satellites in low Earth orbit. Following the successful launches of FACSAT-1 and FACSAT-2, the focus has shifted towards the mission design of FACSAT-3, a constellation consisting of three satellites intended for terrestrial observation, with the possibility of incorporating secondary payloads for various applications. Defining the mission's objective stands as a pivotal step in this process. Specialized literature recommends the analysis of project stakeholders as a fundamental method for establishing the requirements of any space mission. In the case of FACSAT-3, an exhaustive analysis of the needs of these stakeholders was performed through surveys and meetings with numerous participants at the national level. Once these needs were identified, the formulation of the requirements, ensuring that the satellite constellation could fulfill them. With operational and functional requirements in place, the constellation is ready to advance to the design phase. This article presents the methodology implemented these essential preliminary requirements identification within the context of the FACSAT-3 mission. [ABSTRACT FROM AUTHOR]

Recent developments in Distributed Satellite Systems (DSS) have undoubtedly increased mission value due to the ability to reconfigure the spacecraft cluster/formation and incrementally add new or update older satellites in the formation. These features provide inherent benefits, such as increased mission effectiveness, multi-mission capabilities, design flexibility, and so on. Trusted Autonomous Satellite Operation (TASO) are possible owing to the predictive and reactive integrity features offered by Artificial Intelligence (AI), including both on-board satellites and in the ground control segments. To effectively monitor and manage time-critical events such as disaster relief missions, the DSS must be able to reconfigure autonomously. To achieve TASO, the DSS should have reconfiguration capability within the architecture and spacecraft should communicate with each other through an Inter-Satellite Link (ISL). Recent advances in AI, sensing, and computing technologies have resulted in the development of new promising concepts for the safe and efficient operation of the DSS. The combination of these technologies enables trusted autonomy in intelligent DSS (iDSS) operations, allowing for a more responsive and resilient approach to Space Mission Management (SMM) in terms of data collection and processing, especially when using state-of-the-art optical sensors. This research looks into the potential applications of iDSS by proposing a constellation of satellites in Low Earth Orbit (LEO) for near-real-time wildfire management. For spacecraft to continuously monitor Areas of Interest (AOI) in a dynamically changing environment, satellite missions must have extensive coverage, revisit intervals, and reconfiguration capability that iDSS can offer. Our recent work demonstrated the feasibility of AI-based data processing using state-of-the-art on-board astrionics hardware accelerators. Based on these initial results, AI-based software has been successively developed for wildfire detection on-board iDSS satellites. To demonstrate the applicability of the proposed iDSS architecture, simulation case studies are performed considering different geographic locations. [ABSTRACT FROM AUTHOR]

This study presents a mission management technique that is a key component of underwater docking system used to expand the operating range of autonomous underwater vehicle (AUV). We analyzed the docking scenario and AUV operating environment, defining the feasible initial area (FIA) level, event level, and global path (GP) command to improve the rate of docking success and AUV safety. Non-holonomic constraints, mounted sensor characteristic, AUV and mission state, and AUV behavior were considered. Using AUV and docking station, we conducted experiments on land and at sea. The first test was conducted on land to prevent loss and damage of the AUV and verify stability and interconnection with other algorithms; it performed well in normal and abnormal situations. Subsequently, we attempted to dock under the sea and verified its performance; it also worked well in a sea environment. In this study, we presented the mission management technique and showed its performance. We demonstrated AUV docking with this algorithm and verified that the rate of docking success was higher compared to those obtained in other studies.

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This paper presents the design and implementation of BAICal (Intelligent Autonomous Buoy by the University of Calabria), an autonomous surface vehicle (ASV) developed at the Autonomous Systems Lab (LASA) of the Department of Computer Science, Modeling, Electronics, and Systems Engineering (DIMES), University of Calabria. The basic project was born as a research program in marine robotics with multiple applications, either in the sea or in lake/river environments, for data monitoring, search and rescue operations and diver support tasks. Mechanical and hardware designs are discussed by considering a three-degree-of-freedom (3DoF) dynamical model of the vehicle. An extension to the typical guidance, navigation, and control (GNC) software architecture is presented. The software design and the implementation of a manager module (M-GNC architecture) that allows the vehicle to autonomously coordinate missions are described. Indeed, autonomous guidance and movement are only one of several more complex tasks that mobile robots have to perform in a real scenario and that allow a long-term life cycle. Module-based software architecture is developed by using the Robot Operating System (ROS) framework that is suitable for different kinds of autonomous vehicles, such as aerial, ground, surface or underwater drones.

Featured Application: Mission management for cooperative autonomous robotics. Almost every research project that focuses on the cooperation of autonomous robots for underwater operations designs their own architectures. As a result, most of these architectures are tightly coupled with the available robots/vehicles for their respective developments, and therefore the mission plan and management is done using an ad-hoc solution. Typically, this solution is tightly coupled to just one underwater autonomous vehicle (AUV), or a restricted set of them selected for the specific project. However, as the use of AUVs for underwater operations increases, there is the need to identify some commonalities and weaknesses of these architectures, specifically in relation to mission planning and management. In this paper, we review a selected number of architectures and frameworks that in one way or another make use of different approaches to mission planning and management. Most of the selected works were developed for underwater operations. Still, we have included some other architectures and frameworks from other domains that can be of interest for the survey. The explored works have been assessed using selected features related to mission planning and management, considering that underwater operations are performed in an uncertain and unreliable environment, and where unexpected events are not strange. Furthermore, we have identified and highlighted some potential challenges for the design and implementation of mission managers. This provides a reference point for the development of a mission manager component to be integrated in architectures for cooperative robotics in underwater operations, and it can serve for the same purposes in other domains of application. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid route-path planning model for an Autonomous Underwater Vehicle's task assignment and management while the AUV is operating through the variable littoral waters. Several prioritized tasks distributed in a large scale terrain is defined first; then, considering the limitations over the mission time, vehicle's battery, uncertainty and variability of the underlying operating field, appropriate mission timing and energy management is undertaken. The proposed objective is fulfilled by incorporating a route-planner that is in charge of prioritizing the list of available tasks according to available battery and a path-planer that acts in a smaller scale to provide vehicle's safe deployment against environmental sudden changes. The synchronous process of the task assign-route and path planning is simulated using a specific composition of Differential Evolution and Firefly Optimization (DEFO) Algorithms. The simulation results indicate that the proposed hybrid model offers efficient performance in terms of completion of maximum number of assigned tasks while perfectly expending the minimum energy, provided by using the favorable current flow, and controlling the associated mission time. The Monte-Carlo test is also performed for further analysis. The corresponding results show the significant robustness of the model against uncertainties of the operating field and variations of mission conditions. [ABSTRACT FROM AUTHOR]

Abstract Advances in hardware technology have enabled more integration of sophisticated software, triggering progresses in development and employment of Unmanned Vehicles (UVs), and mitigating restraints for onboard intelligence. As a result, UVs can now take part in more complex mission where continuous transformation in environmental condition calls for higher level of situational responsiveness. This paper serves as an introduction to UVs mission planning and management systems aiming to highlight some of the recent developments in the field of autonomous underwater and aerial vehicles in addition to stressing some possible future directions and discussing the learned lessons. A comprehensive survey over autonomy assessment of UVs, and different aspects of autonomy such as situation awareness, cognition, and decision-making has been provided in this study. The paper separately explains the humanoid and autonomous system's performance and highlights the role and impact of a human in UVs operations. [ABSTRACT FROM AUTHOR]

Expansion of today's underwater scenarios and missions necessitates the requisition for robust decision making of the autonomous underwater vehicle (AUV); hence, design an efficient decision-making framework is essential for maximizing the mission productivity in a restricted time. This paper focuses on developing a deliberative conflict-freetask assignment architecture encompassing a global route planner (GRP) and a local path planner (LPP) to provide consistent motion planning encountering both environmental dynamic changes and a priori knowledge of the terrain, so that the AUV is reactively guided to the target of interest in the context of an uncertain underwater environment. The architecture involves three main modules: The GRP module at the top level dealswith the task priority assignment, mission time management, and determination of a feasible route between start and destination point in a large-scale environment. The LPP module at the lower level deals with safety considerations and generates collision-free optimal trajectory between each specific pair of waypoints listed in obtained global route. Re-planning module tends to promote robustness and reactive ability of the AUV with respect to the environmental changes. The experimental results for different simulated missions demonstrate the inherent robustness and drastic efficiency of the proposed scheme in enhancement of the vehicles autonomy in terms of mission productivity, mission time management, and vehicle safety. [ABSTRACT FROM AUTHOR]

Almost every research project that focuses on the cooperation of autonomous robots for underwater operations designs their own architectures. As a result, most of these architectures are tightly coupled with the available robots/vehicles for their respective developments, and therefore the mission plan and management is done using an ad-hoc solution. Typically, this solution is tightly coupled to just one underwater autonomous vehicle (AUV), or a restricted set of them selected for the specific project. However, as the use of AUVs for underwater operations increases, there is the need to identify some commonalities and weaknesses of these architectures, specifically in relation to mission planning and management. In this paper, we review a selected number of architectures and frameworks that in one way or another make use of different approaches to mission planning and management. Most of the selected works were developed for underwater operations. Still, we have included some other architectures and frameworks from other domains that can be of interest for the survey. The explored works have been assessed using selected features related to mission planning and management, considering that underwater operations are performed in an uncertain and unreliable environment, and where unexpected events are not strange. Furthermore, we have identified and highlighted some potential challenges for the design and implementation of mission managers. This provides a reference point for the development of a mission manager component to be integrated in architectures for cooperative robotics in underwater operations, and it can serve for the same purposes in other domains of application.

Abstract: This paper presents the design, implementation and real world evaluation of an autonomous underwater vehicle (AUV). The mission of the vehicle is to carry out an ocean survey in dynamic, partially unknown and unsafe environment, and subject to constraints on the operations. It is a multi-area and multi-sensor-type survey mission which is appropriate for a large range ocean survey to obtain different parameters in different objective areas. The main work in this project is the novel design and development of a hierarchical on-board architecture of the AUV. The architecture is specified by increasingly detailed Petri nets (PN) under the agent-based distributed autonomous control structure. A number of agents have been used in the architecture for mission management and control. Communications and cooperation between agents are realised. The management and control of the mission is modelled by discrete events driven PN formalism. The highest level PN and lower sub-PNs with designed events are described in detail. The designed vehicle has been tested in real world experiments, a lake trial, to evaluate its performance. The feasibility and effectiveness of the architecture is proven in the lake trials in nominal and degraded situations. [Copyright &y& Elsevier]

Abstract: Unmanned Aircraft Systems (UAS) have great potential to be used in a wide variety of applications, such as environmental applications, emergency situations and surveillance tasks, among others. However, most current UAS solutions, if not remotely piloted, rely on waypoint based flight control systems for their navigation and are unable to coordinate the aircraft flight with payload operation. We believe that increased automation, together with reconfiguration capabilities and cost-effectiveness, are key requirements for UAS to be successful in a commercial domain. The resulting platform should be affordable and able to operate in different application scenarios with reduced development effort and human intervention. In this paper, an architecture for providing UAS platforms with reconfigurable automated behavior is presented. The desired automation and reconfiguration capabilities are built upon the core sub-systems in that architecture: the Flight Plan Manager and the Mission Manager. Both systems are part of a wider set of embarked services that manage UAS operations during the mission. The Flight Plan Manager and the Mission Manager are respectively responsible for governing the UAS flight and orchestrating operation of other services on-board the UAS. There are two distinct features of the system: firstly, UAS behavior is not hard-coded into its software components, but described using specification formalisms; secondly, the UAS flight path is described by means of an XML based language specifically designed for this purpose. With this approach, flight and payload behavior are described in separate documents that complement each other. Prototype implementations of these services have been implemented and used to validate the proposed specification and execution methods with an application example devoted to the monitoring of wildfires. [Copyright &y& Elsevier]

The advent of mobile and ubiquitous systems has enabled the development of autonomous systems such as wireless-sensors for environmental data collection and teams of collaborating Unmanned Autonomous Vehicles (UAVs) used in missions unsuitable for humans. However, with these range of new application-domains comes a new challenge-enabling self-management in mobile autonomous systems. Autonomous systems have to be able to manage themselves individually as well as form self-managing teams which are able to adapt to failures, protect themselves from attacks and optimise performance. This paper proposes a novel distributed policy-based framework that enables autonomous systems of varying scale to perform self-management individually and as a team. The framework allows missions to be specified in terms of roles in an adaptable and reusable way, enables dynamic and secure team formation with a utility-based approach for optimal role assignment, caters for communication link maintenance amongst team-members and recovery from failure. Adaptive management is achieved by employing a policy-based architecture to enable dynamic modification of the management strategy relating to resources, role behaviour, communications and team management, without interrupting the basic software within the system. Evaluation of the framework shows that it is scalable with respect to the number of roles, and consequently the number of autonomous systems involved in the mission. It is also optimal with respect to role assignments, and robust to intermittent communication link and permanent team-member failures. [ABSTRACT FROM AUTHOR]

This article concerns the problem of managing the new generation of Agile Earth Observing Satellites (AEOS). This kind of satellites is presently studied by the French Centre National d'E´tudes Spatiales (PLEIADES project). The mission of an Earth Observing Satellite is to acquire images of specified areas on the Earth surface, in response to observation requests from customers. Whereas non-agile satellites such as SPOT5 have only one degree of freedom for acquiring images, the new generation satellites have three, giving opportunities for a more efficient use of the satellite imaging capabilities. Counterwise to this advantage, the selection and scheduling of observations becomes significantly more difficult, due to the larger search space for potential solutions. Hence, selecting and scheduling observations of agile satellites is a highly combinatorial problem. This article sets out the overall problem and analyses its difficulties. Then it presents different methods which have been investigated in order to solve a simplified version of the complete problem: a greedy algorithm, a dynamic programming algorithm, a constraint programming approach and a local search method. [Copyright &y& Elsevier]

As a part of the 2000-01 American Dental Education Association (ADEA) Leadership Institute, the Leadership Institute Fellows conducted a faculty development workshop for department chairpersons and program directors during the 2001 ADEA Annual Session. A central premise of the workshop was that successful chairpersons and program directors are both effective leaders and effective managers and that leadership and management involve complementary activities. The workshop was casebased. The ADEA Leadership Institute Fellows developed the cases and led roundtable discussions of each case. A group facilitator led large group debriefings to apply management and leadership theory to each case. The purpose of this paper is to review leadership challenges and management concepts as they were applied in a case-based faculty development workshop. The program was structured to address leadership challenges relating to managing people, mission management, conflict recognition, and conflict management. The cases were developed to relate management theories to situations in academic administration. The situations were designed to encourage debate from numerous perspectives. Each case presented general dilemmas that could be addressed from the vantage point of the dean, chair, or individual faculty member. Reinforcing discussion followed and included identification of central issues, key management concepts, and action alternatives. Because of the breadth of possible discussion, group case analyses at the workshop and in the appended case reviews explore only one perspective. This overview article introduces concepts of leadership and management that provide the foundation for analysis of three case studies that follow. These cases address common leadership and management issues in academic dentistry through three typical cases: the frustrated faculty member (case 1), the misdirected faculty member (case 2), and the faculty member stuck in the middle (case 3). [ABSTRACT FROM AUTHOR]