In this paper, we describe an approach to large-scale space structure assembly frameworks, keeping in mind the many benefits associated with the use of autonomous crawling mobile robots.

Our research presents a model of a large-scale deployable structure, along with its physical constraints, and a corresponding assembly approach. Initially, all building elements (beams and nodes) are stored in the launcher fairing. These will be deployed to form the structure on which the robots themselves will evolve until the final configuration is reached. The proposed concept considers a structure made up of truss beams with standard interfaces at their ends and attachment nodes, also equipped with standard interfaces, supporting a payload such as a solar panel or a deployable antenna. Assembly is performed by crawling robots, which are autonomous systems that adhere to or grip the structure and move around it. However, the robot's plan, spacecraft's actuators, and payload structure should be carefully co-designed to ensure manageable and stable dynamics.

Therefore, we represent the assembling problem as an automated planning instance, where several structural constraints dictate the actions available for execution, and their application is constrained in time to avoid introducing dynamic forces that compromise stability and pointing accuracy.

The automated planner algorithm provides a step-by-step sequence to achieve the final deployed structure. This algorithm utilizes a cost function that evaluates the time of each task by considering the spacecraft's actuator capabilities. Subsequently, FEM tools are employed to verify if the plan's execution time respects the structural constraints. If not, a trade-off is sought between slowing down the robot or increasing the rigidity of structural elements.

We have implemented a prototype of the planner to validate its effectiveness. We have also detailed the models and assumptions used to estimate structural constraints and task times. Additionally, we have illustrated the FEM validation test to demonstrate the accuracy of our approach.

This model and its associated tools help to illustrate the feasibility of the approach and the benefits of having AI tools for autonomous assembly robots in space.