Litcius/Paper detail

Autogenetic Gravity Center Placement

Timothy Sands

2025Sensors9 citationsDOIOpen Access PDF

Abstract

Operations by space drones mandate significant autonomy. This study experimentally evaluates key proposed applications of autonomy. Center of gravity auto-location is proposed using autonomous identification of mass properties, necessitating nonlinear state estimation. Nonlinear, coupled governing kinetics are strictly adopted as the control, and inversion provides closed-form estimates of mass properties. Seminally neglecting the diagonal inertia moments, the inertia cross-products are utilized to exactly find the mass center coordinates using the parallel axis theorem to parameterize the location coordinates. In December 2024, experiments were performed in space for hours, validating the approaches proposed. The findings indicate the longitudinal distribution was quite symmetric. Meanwhile, the lateral distribution was quite off-balance. Estimation convergence of the mass center coordinates was improved compared to the state-of-the-art comparative benchmark. In hundreds of days, the latter achieved millimeter convergence, while in minutes, the former achieved hundreds of millimeters convergence.

Topics & Concepts

Convergence (economics)Nonlinear systemCenter of mass (relativistic)DiagonalBenchmark (surveying)Control theory (sociology)Applied mathematicsMathematical analysisMathematicsComputer scienceGeodesyClassical mechanicsGeometryPhysicsGeographyControl (management)Artificial intelligenceEconomicsEconomic growthQuantum mechanicsEnergy–momentum relationInertial Sensor and NavigationSpace Satellite Systems and ControlRobotics and Sensor-Based Localization