TY - JOUR
T1 - A Multi-Mode Navigation Method for Space Robots to Capture a Tumbling Target
AU - Che, Dejia
AU - Zheng, Zixuan
AU - Yuan, Jianping
N1 - Publisher Copyright:
Copyright © 2022 by the International Astronautical Federation (IAF). All rights reserved.
PY - 2022
Y1 - 2022
N2 - An uncooperative space target may be in different motion modes when a space robot attempts to capture it, such as being in contact with the robot, colliding with it, or float freely. Almost all conventional state estimation methods are oriented towards a single motion mode. Therefore, the robot has to switch algorithms according to the mode of movement during a removal mission with multiple modes, which negatively affect convergence speed and stability of the estimation. To develop a navigation method suitable for multiple motion modes, two basic strategies that are independent of the robot-target interaction are integrated. Using the momentum conservation law (MC), dynamic equations of the target-robot combination are derived. The momentum and the angular momentum of the combination are included in the state vector, simplifying the derivation. The second strategy employs continuous vision guidance to correct model predictions based on the Cubature Kalman filter (CKF). After analyzing the observability and the stability of the multi-mode estimator, two vectors are derived to indicate whether or not parts of the inertia parameters of the target can be estimated by the estimator. Several motion modes are simulated in the paper which shows that by employing the two strategies, a single Kalman filter used in the navigation technique can always estimate motion states of the target. The results of the observability analysis are also demonstrated in the simulation.
AB - An uncooperative space target may be in different motion modes when a space robot attempts to capture it, such as being in contact with the robot, colliding with it, or float freely. Almost all conventional state estimation methods are oriented towards a single motion mode. Therefore, the robot has to switch algorithms according to the mode of movement during a removal mission with multiple modes, which negatively affect convergence speed and stability of the estimation. To develop a navigation method suitable for multiple motion modes, two basic strategies that are independent of the robot-target interaction are integrated. Using the momentum conservation law (MC), dynamic equations of the target-robot combination are derived. The momentum and the angular momentum of the combination are included in the state vector, simplifying the derivation. The second strategy employs continuous vision guidance to correct model predictions based on the Cubature Kalman filter (CKF). After analyzing the observability and the stability of the multi-mode estimator, two vectors are derived to indicate whether or not parts of the inertia parameters of the target can be estimated by the estimator. Several motion modes are simulated in the paper which shows that by employing the two strategies, a single Kalman filter used in the navigation technique can always estimate motion states of the target. The results of the observability analysis are also demonstrated in the simulation.
KW - motion mode
KW - relative navigation
KW - space robot
KW - uncooperative target
UR - http://www.scopus.com/inward/record.url?scp=85167590813&partnerID=8YFLogxK
M3 - 会议文章
AN - SCOPUS:85167590813
SN - 0074-1795
VL - 2022-September
JO - Proceedings of the International Astronautical Congress, IAC
JF - Proceedings of the International Astronautical Congress, IAC
T2 - 73rd International Astronautical Congress, IAC 2022
Y2 - 18 September 2022 through 22 September 2022
ER -