Research/ SPACE AI & AUTONOMY
Autonomous Spacecraft Mission Planning And Execution In A Petri Net Framework
A. Indra
Autonomy, Task Planning & OperationsOpenAlex topic: AI-based Problem Solving and Planning · Multi-Robot & SwarmsOpenAlex keyword: multi-agent systems
Presently, most spacecraft are controlled from ground involving activities such as up-linking the schedule of daily operations and monitoring health parameters. These activities lead to a cognitive overload on human operators. Imaging/science opportunities are lost, if any discrepancies occur during the execution of pre-planned sequences. Consequently, advanced space exploration systems for future needs demand on-board intelligence and autonomy. This thesis attempts to solve the problem of providing an adequate degree of autonomy in future generation of spacecraft. The autonomous spacecraft accept high-level goals from users and make decisions on-board to generate detailed command schedules satisfying stringent constraints posed by the harsh environment of the space, visibility criteria and scarce on-board resources. They reconfigure themselves in case of any failure and re-plan when needed. Autonomy concepts are derived in the context of complex systems by drawing analogy to living organisms and social organisations. A general autonomy framework may be defined with a six level structure comprising of the following capabilities -reflexes, awareness, self-regulation, self-healing, self-adaptation and self-evolution. A generic and reusable software architecture is proposed using hybrid multi-agent systems, which are arranged in a hierarchical manner using two types of decomposition viz. stratum and layer. The software architecture of the autonomous spacecraft is modeled as a stratified agent with a deliberative stratum, which achieves adaptive behaviour and a reactive stratum, which achieves reactive behaviour. Each individual agent has a generic structure comprising of perception, action, communication and knowledge components. It achieves the specialist capability through model-based reasoning. The knowledge models encompass: Planning knowledge describing higher-level goals, task structure and method of achieving the goals, Control knowledge encompassing the static and dynamic models of the spacecraft and Diagnostic knowledge incorporating the cause-effect relationships. The deliberative stratum is capable of planning in different time horizons and is, in turn, organised into a hierarchical agent system with three layers corresponding to different time horizons. It is composed of a long-term, medium-term and short-term planning agents, focusing on strategic issues, spacecraft level resources and specific spacecraft states respectively. The power of Petri nets is exploited for knowledge modeling as well as for plan representation. The ability of Petri nets to represent causality, concurrency and conflict relations explicitly makes it an excellent tool for representing the planning problem. Hierarchical Timed Petri Net is chosen for our modeling, since it captures the temporal requirements of the real-time spacecraft operations as well as facilitates the modeling of the system with multiple levels of abstraction. The necessary primitives for the plan representation are defined. In hierarchical modeling using Petri…