[논문]Experimental Study of Spacecraft Pose Estimation Algorithm Using Vision-based Sensor

Hyun, Jeonghoon; Eun, Youngho; Park, Sang-Young

doi:10.5140/jass.2018.35.4.263

Experimental Study of Spacecraft Pose Estimation Algorithm Using Vision-based Sensor 원문보기

Journal of astronomy and space sciences, v.35 no.4, 2018년, pp.263 - 277

Hyun, Jeonghoon (Department of Astronomy, Yonsei University) , Eun, Youngho (Department of Astronomy, Yonsei University) , Park, Sang-Young (Department of Astronomy, Yonsei University)

Abstract ▼ AI-Helper

This paper presents a vision-based relative pose estimation algorithm and its validation through both numerical and hardware experiments. The algorithm and the hardware system were simultaneously designed considering actual experimental conditions. Two estimation techniques were utilized to estimate relative pose; one was a nonlinear least square method for initial estimation, and the other was an extended Kalman Filter for subsequent on-line estimation. A measurement model of the vision sensor and equations of motion including nonlinear perturbations were utilized in the estimation process. Numerical simulations were performed and analyzed for both the autonomous docking and formation flying scenarios. A configuration of LED-based beacons was designed to avoid measurement singularity, and its structural information was implemented in the estimation algorithm. The proposed algorithm was verified again in the experimental environment by using the Autonomous Spacecraft Test Environment for Rendezvous In proXimity (ASTERIX) facility. Additionally, a laser distance meter was added to the estimation algorithm to improve the relative position estimation accuracy. Throughout this study, the performance required for autonomous docking could be presented by confirming the change in estimation accuracy with respect to the level of measurement error. In addition, hardware experiments confirmed the effectiveness of the suggested algorithm and its applicability to actual tasks in the real world.

주제어

표/그림 (22)

표 Table 1. Camera(DFK33UX174) and lens (GMTHR48014MCN)
그림 Fig. 1. 2D Gray scale image obtained by image processing.
그림 Fig. 2. Singularity (Rodgers 2006).
그림 Fig. 3. LED configuration considering singularity, field of view, and minimum distance.
그림 Fig. 4. Cutoff and centroiding.
그림 Fig. 5. Centroiding error (left), measurement error with respect to relative distance (right).
그림 Fig. 6. LDM41.1(Jenoptik) (left), distance measurement error of laser (right).
그림 Fig. 7. The error of position (above), velocity (below), control (left), and estimation (right) with 1 pixel measurement error.
표 Table 2. Initial state (above), docking requirement (below)
표 Table 3. The performance of position and attitude according to the level of measurement error
그림 Fig. 8. The error of attitude (above), angular velocity (below), control (left), and estimation (right) with 1 pixel measurement error.
표 Table 4. Initial state of PCO scenario
그림 Fig. 9. Attitude control error of chief spacecraft including camera.
그림 Fig. 10. The accuracy of relative position estimation with laser distance meter.
그림 Fig. 11. The accuracy of relative velocity estimation with laser distance meter.
표 Table 5. The accuracy of attitude estimation (above), position and velocity estimation (below)
그림 Fig. 12. Reference using infrared cameras.
그림 Fig. 13. True relative attitude confirmed by infrared cameras.
그림 Fig. 14. True relative position confirmed by infrared cameras.
그림 Fig. 15. Relative attitude estimation error.
그림 Fig. 16. Relative position estimation error.
그림 Fig. 17. Image distortion due to misalignment of attitude.

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제안 방법

It is confirmed that the relative position estimation accuracy decreases remarkably when considering nonlinear perturbations (Lee & Pernicka 2011). In this study, a projected circular orbit (PCO) formation flying scenario was implemented by applying nonlinear perturbations and possible degradation of the sensor resolution in reality.
In this study, pose alignment was implemented by the vision system in numerical simulations to verify the feasibility of the system, i.e., that it can be applied to satellite formation flying. The influence of external environmental factors on the performance of formation flying was analyzed, while checking the estimation and control accuracy according to the level of observation error.
, that it can be applied to satellite formation flying. The influence of external environmental factors on the performance of formation flying was analyzed, while checking the estimation and control accuracy according to the level of observation error. In order to improve the relative position estimation accuracy even in the presence of nonlinear perturbation, we proposed a performance improvement by combination with a laser sensor.

이론/모형

1999). The relative state between spacecraft can be estimated by using the nonlinear least squares method (Junkins et al. 1999) or the extended Kalman filter (Kim et al. 2007). In addition, a study was conducted for estimation of both the state of a chief and a deputy satellite based on chief coordinates rather than local vertical and local horizontal (LVLH) coordinates (Zhang et al.

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