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.
Document Type
Event
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.