Hardware-In-the-loop Simulation Framework for CubeSats Proximity Operations: Application to the Milani Mission

Milani is a 6U CubeSat that will be released by Hera in proximity of the Didymos binary asteroid. The spacecraft will demonstrate autonomous Guidance Navigation and Control (GNC) capability for CubeSats in deep space, enhancing the scientific outcome of the mission. The Deep-space Astrodynamics Research and Technology (DART) Group at Politecnico di Milano is responsible for Milani Mission Analysis (MA), GNC and Image Processing (IP) design. Operations in proximity of minor bodies demand high levels of autonomy to achieve cost-effective, safe, and reliable solutions. The on-board software has a central role in these applications, thus it must be extensively tested and validated to satisfy mission requirements and to guarantee robustness to uncertainties. A robust and standardized methodology to design, validate, and test vision-based Attitude and Orbit Control Systems (AOCS) algorithms is fundamental to achieve fast prototyping while facing at the same time limited availability of resources and time. This paper presents a modular and flexible approach, developed at DART lab, to test GNC algorithms with camera- and processor-in-the-loop simulations. This framework is characterized by three elements: 1) a functional engineering simulator for six-degrees-of-freedom closed-loop analyses, 2) a vision-based navigation test-bench for camera-in-the-loop simulations, and 3) a single-board computer to test the algorithm in a representative computational environment. The first element is the modular CUBesat ORbit and GNC (CUBORG) tool, developed in MATLAB/Simulink. This contains a high-fidelity model of the environment suitable for simulating different operative scenarios, and a prototype of the spacecraft AOCS. Camera-in-the loop simulations are performed thanks to the in-house developed Tiny Versatile 3D Reality Simulation Environment (TinyV3RSE). This is composed of a high-resolution screen which displays synthetic images as they would be acquired from the probe during the mission, and stimulates, through a collimator, the camera mounted in the facility. The third element is a Raspberry Pi which is selected as external board to run processor-in-the-loop simulations. The proposed approach is tested on the Milani case simulating the GNC and IP subsystems in a real-hardware environment, doing a step forward towards the hardware-in-the-loop validation and verification of them.