Session

Session VI: FJR Student Competition -Research & Academia

Location

Salt Palace Convention Center, Salt Lake City, UT

Abstract

This paper presents a hardware-in-the-loop (HIL) simulation framework designed for the rapid evaluation and qualification of commercial off-the-shelf (COTS) sensors in small satellite Rendezvous and Proximity Operations (RPO). The proposed system supports 2U to 6U CubeSat platforms and enables subsystem-level testing by integrating a real-time mechanical simulator with a software-defined dynamic environment. The setup replicates target satellite motion using a custom 3-DOF rig driven by stepper motors and supports configurable sensor parameters, motion profiles, and automated parameter sweeps. A Microsoft Kinect v2 sensor captures RGB, IR, and depth data, enabling multi-spectral evaluation under varied illumination and material reflectivity conditions. Preliminary results demonstrate successful closed-loop estimation of satellite attitude using edge-based pose tracking. Compared to traditional RPO testbeds such as air-bearing platforms, this low-cost, modular framework reduces development time, eliminates the need for high-fidelity digital twins, and supports rapid testing of vision-based navigation algorithms. The architecture also enables scalable training data generation for machine learning-based systems and supports future enhancements, including automated center-of-gravity adjustments and dynamic sensor positioning.

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Aug 13th, 11:45 AM

Hardware in the Loop Simulation for Commercial Off the Shelf Sensor Qualification in Small Satellite Rendezvous and Proximity Operations

Salt Palace Convention Center, Salt Lake City, UT

This paper presents a hardware-in-the-loop (HIL) simulation framework designed for the rapid evaluation and qualification of commercial off-the-shelf (COTS) sensors in small satellite Rendezvous and Proximity Operations (RPO). The proposed system supports 2U to 6U CubeSat platforms and enables subsystem-level testing by integrating a real-time mechanical simulator with a software-defined dynamic environment. The setup replicates target satellite motion using a custom 3-DOF rig driven by stepper motors and supports configurable sensor parameters, motion profiles, and automated parameter sweeps. A Microsoft Kinect v2 sensor captures RGB, IR, and depth data, enabling multi-spectral evaluation under varied illumination and material reflectivity conditions. Preliminary results demonstrate successful closed-loop estimation of satellite attitude using edge-based pose tracking. Compared to traditional RPO testbeds such as air-bearing platforms, this low-cost, modular framework reduces development time, eliminates the need for high-fidelity digital twins, and supports rapid testing of vision-based navigation algorithms. The architecture also enables scalable training data generation for machine learning-based systems and supports future enhancements, including automated center-of-gravity adjustments and dynamic sensor positioning.