Prototyping Operational Autonomy for Space Traffic Management

Current state of the art in Space Traffic Management (STM) relies on a handful of providers for surveillance and collision prediction, and manual coordination between operators. Neither is scalable to support the expected 10x increase in spacecraft population in less than 10 years, nor does it support automated manuever planning. We present a software prototype of an STM architecture based on open Application Programming Interfaces (APIs), drawing on previous work by NASA to develop an architecture for low-altitude Unmanned Aerial System Traffic Management. The STM architecture is designed to provide structure to the interactions between spacecraft operators, various regulatory bodies, and service suppliers, while maintaining flexibility of these interactions and the ability for new market participants to enter easily. Autonomy is an indispensable part of the proposed architecture in enabling efficient data sharing, coordination between STM participants and safe flight operations. Examples of autonomy within STM include syncing multiple non-authoritative catalogs of resident space objects, or determining which spacecraft maneuvers when preventing impending conjunctions between multiple spacecraft. The STM prototype is based on modern micro-service architecture adhering to OpenAPI standards and deployed in industry standard Docker containers, facilitating easy communication between different participants or services. The system architecture is designed to facilitate adding and replacing services with minimal disruption. We have implemented some example participant services (e.g. a space situational awareness provider/SSA, a conjunction assessment supplier/CAS, an automated maneuver advisor/AMA) within the prototype. Different services, with creative algorithms folded into then, can fulfil similar functional roles within the STM architecture by flexibly connecting to it using pre-defined APIs and data models, thereby lowering the barrier to entry of new players in the STM marketplace. We demonstrate the STM prototype on a multiple conjunction scenario with multiple maneuverable spacecraft, where an example CAS and AMA can recommend optimal maneuvers to the spacecraft operators, based on a predefined reward function. Such tools can intelligently search the space of potential collision avoidance maneuvers with varying parameters like lead time and propellant usage, optimize a customized reward function, and be implemented as a scheduling service within the STM architecture. The case study shows an example of autonomous maneuver planning is possible using the API-based framework. As satellite populations and predicted conjunctions increase, an STM architecture can facilitate seamless information exchange related to collision prediction and mitigation among various service applications on different platforms and servers. The availability of such an STM network also opens up new research topics on satellite maneuver planning, scheduling and negotiation across disjoint entities

Autonomous vehicles in the response to maritime incidents

The future role of autonomous vehicles in the emergency response to maritime incidents isdiscussed and a framework for their integration into existing response plans is proposed. This is done inthe context of the developments on autonomous vehicle systems from the Underwater Systems andTechnologies Laboratory from Porto University

Agoric computation: trust and cyber-physical systems

In the past two decades advances in miniaturisation and economies of scale have led to the emergence of billions of connected components that have provided both a spur and a blueprint for the development of smart products acting in specialised environments which are uniquely identifiable, localisable, and capable of autonomy. Adopting the computational perspective of multi-agent systems (MAS) as a technological abstraction married with the engineering perspective of cyber-physical systems (CPS) has provided fertile ground for designing, developing and deploying software applications in smart automated context such as manufacturing, power grids, avionics, healthcare and logistics, capable of being decentralised, intelligent, reconfigurable, modular, flexible, robust, adaptive and responsive. Current agent technologies are, however, ill suited for information-based environments, making it difficult to formalise and implement multiagent systems based on inherently dynamical functional concepts such as trust and reliability, which present special challenges when scaling from small to large systems of agents. To overcome such challenges, it is useful to adopt a unified approach which we term agoric computation, integrating logical, mathematical and programming concepts towards the development of agent-based solutions based on recursive, compositional principles, where smaller systems feed via directed information flows into larger hierarchical systems that define their global environment. Considering information as an integral part of the environment naturally defines a web of operations where components of a systems are wired in some way and each set of inputs and outputs are allowed to carry some value. These operations are stateless abstractions and procedures that act on some stateful cells that cumulate partial information, and it is possible to compose such abstractions into higher-level ones, using a publish-and-subscribe interaction model that keeps track of update messages between abstractions and values in the data. In this thesis we review the logical and mathematical basis of such abstractions and take steps towards the software implementation of agoric modelling as a framework for simulation and verification of the reliability of increasingly complex systems, and report on experimental results related to a few select applications, such as stigmergic interaction in mobile robotics, integrating raw data into agent perceptions, trust and trustworthiness in orchestrated open systems, computing the epistemic cost of trust when reasoning in networks of agents seeded with contradictory information, and trust models for distributed ledgers in the Internet of Things (IoT); and provide a roadmap for future developments of our research

A flight software development and simulation framework for advanced space systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2002.Includes bibliographical references (p. 293-302).Distributed terrestrial computer systems employ middleware software to provide communications abstractions and reduce software interface complexity. Embedded applications are adopting the same approaches, but must make provisions to ensure that hard real-time temporal performance can be maintained. This thesis presents the development and validation of a middleware system tailored to spacecraft flight software development. Our middleware runs on the Generalized Flight Operations Processing Simulator (GFLOPS) and is called the GFLOPS Rapid Real-time Development Environment (GRRDE). GRRDE provides publish-subscribe communication services between software components. These services help to reduce the complexity of managing software interfaces. The hard real-time performance of these services has been verified with General Timed Automata modelling and extensive run-time testing. Several example applications illustrate the use of GRRDE to support advanced flight software development. Two technology-focused studies examine automatic code generation and autonomous fault protection within the GRRDE framework. A complex simulation of the TechSat 21 distributed spacebased radar mission highlights the utility of the approach for large-scale applications.by John Patrick Enright.Ph.D

System Integration and Optimization Model (SIOM)

Modern high tech greenhouses are a combination of various technical systems. There are more and more interactions between those systems. Therefore it is hard to adapt greenhouse design to another climate/situation. There is a need for a decision support system, combining practical know how, local parameters, available design models and validation data. This decision support system should also support growers in optimizing their business case. A publish/subscribe framework originally designed for urban planning is adjusted for the greenhouse design application. Design models such as climate, light, economy, crop growth are connected to this framework. In a case study the functioning of the framework is illustrated. The publish/subscribe framework is an easy way of connecting a wide range of existing design models. It requires low maintenance, several models with different abstraction level can be connected and models can be exchanged easily. The publish/ subscribe approach allow parallel processing, speeding up calculation time. SIOM is an effective approach to combine knowledge stored in various design models and gives an end user insight in the consequences of their design choices. Validation of the results, additional design models and a design process scheme is needed to make SIOM applicable by greenhouse builders