Proceedings of the 1994 IEEE International Conference on Robotics and Automation
DOI: 10.1109/robot.1994.351227
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Motion estimation of unknown rigid body under no external forces and moments

Abstract: This paper presents a method t o estimate and to predict general three-dimensional motions of an unknown rigid body under no external forces and moments using visual information, which is applicable to autonomous space robotic missions. Four parameters of dynamics and a reference coordinate frame to describe the motion are computed based on the Euler's equation of motion from a sequence of angular velocity vectors extracted from diflerence of images. Through computer simulations for variovs kinds of motions th… Show more

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Cited by 27 publications
(19 citation statements)
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“…The method was used in the estimation part of a tracking control scheme in [59]. Assuming that an object is not acted upon by any external force and moment, the motion of the target satellite was predicted in [60]. Litcher and Dubowsky, using 3-D vision sensors, proposed an architecture for estimation of dynamic state, geometric shape, and model parameters of an object in orbit, with potential application to a satellite capturing [61].…”
Section: A Target Motion Prediction and Parameter Identificationmentioning
confidence: 99%
“…The method was used in the estimation part of a tracking control scheme in [59]. Assuming that an object is not acted upon by any external force and moment, the motion of the target satellite was predicted in [60]. Litcher and Dubowsky, using 3-D vision sensors, proposed an architecture for estimation of dynamic state, geometric shape, and model parameters of an object in orbit, with potential application to a satellite capturing [61].…”
Section: A Target Motion Prediction and Parameter Identificationmentioning
confidence: 99%
“…Ghosh et al [9] use estimation theory to recover the riccati dynamics and shape of planar objects using optical flow. Masutani et al [15] describes an algorithm to extract the inertial parameters of a tumbling rigid body from video. Their system tracks feature points in the images to get instantaneous velocity measurements and uses the Poinsot's solution [22] to compute the inertial parameters.…”
Section: Related Workmentioning
confidence: 99%
“…Using this framework, we show how it is possible to simultaneously compute the object, camera, and environment parameters from video data. Unlike previous analytical methods [15,14], our method does not require any velocity, acceleration, or torque measurements to compute the body state as a function of time. Furthermore, an important element of our estimation approach is that it relies only on easily computable metrics such as image silhouettes and 2D bounding boxes, avoiding the need to compute optical flow or track features on the object over time.…”
Section: Introductionmentioning
confidence: 99%
“…This is in principle possible for a rigid body moving in the absence of forces and torques, even if it does not possess an axis of symmetry which facilitates its motion. However, an explicit solution suitable for numerical implementation seems to be missing in the literature (although partial answers are abundant [9,10,11,12,13,14]). For this reason, we will present the explicit solution here.…”
Section: Introductionmentioning
confidence: 99%