Joint axis and position estimation from inertial measurement data by exploiting kinematic constraints

Seel, Thomas; Schauer, Thomas; Raisch, Jörg

doi:10.1109/cca.2012.6402423

Cited by 117 publications

(113 citation statements)

References 7 publications

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“…The optimization problem (15) can be solved efficiently using a Gauss-Newton method [8] as shown in [4], which makes use of the partial derivatives ∂e(k, r)…”

Section: B Estimation Using Iterative Optimization Methodsmentioning

confidence: 99%

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Experimental evaluation of joint position estimation using inertial sensors

Olsson

Halvorsen

2017

2017 20th International Conference on Information Fusion (Fusion)

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Abstract-In this paper we study the problem of estimating the position of a joint that is connecting two rigid links in a biomechanical model. By equipping the two links with inertial sensors, which measure linear acceleration and angular velocity, it is possible to estimate the joint position. Estimation methods for this problem have been proposed before, but experimental evaluation and comparison between methods is lacking. The main contribution of this paper is an experimental evaluation of three different methods, a least-squares method and two iterative optimization methods that minimize a sum of squared errors and a sum of absolute errors. The iterative methods turns out to be superior to the least-squares method. Minimizing the sum of squared errors is faster but not as robust against outliers as minimizing the sum of absolute errors.

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“…The optimization problem (15) can be solved efficiently using a Gauss-Newton method [8] as shown in [4], which makes use of the partial derivatives ∂e(k, r)…”

Section: B Estimation Using Iterative Optimization Methodsmentioning

confidence: 99%

“…Similar problems have been studied previously in e.g. [4], [5], [6], but experimental evaluation and comparisons of the methods are lacking. Our main contribution with this paper is the experimental evaluation of three possible methods for estimating the joint position using the two inertial sensors.…”

Section: Introductionmentioning

confidence: 97%

Experimental evaluation of joint position estimation using inertial sensors

Olsson

Halvorsen

2017

2017 20th International Conference on Information Fusion (Fusion)

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“…Joint positions and angles are calculated based on the exploitation of kinematic constraints. The advantage of these newly developed algorithms is that they are neither depended on an exact mounting orientation of the sensors in relation to the body segments nor on exact calibration movements [4].…”

Section: Methodsmentioning

confidence: 99%

A Mobile Gait Analysis System for Optimization of Prosthetic Alignments

Westebbe

Thiele

Kraft

2013

Biomedical Engineering / Biomedizinische Technik

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“…14 In addition, some theories focus on the consideration about the effect of the joint errors, and the link errors on the manipulator position and orientation compensation have achieved good results. [15][16][17] In this article, because we want to do the error compensation based on the actual pose information which is measured by IMU from manipulator end-effector, so we established error model by using a generalized error method, 14 and focus on the relationship between actual pose and theory pose of manipulator end-effector.…”

Section: Manipulator Kinematics Modelmentioning

confidence: 99%

Inertial measurement unit–based iterative pose compensation algorithm for low-cost modular manipulator

Lin

Min

Wei

2016

Advances in Mechanical Engineering

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It is a necessary mean to realize the accurate motion control of the manipulator which uses end-effector pose correction method and compensation method. In this article, first, we established the kinematic model and error model of the modular manipulator (WUST-ARM), and then we discussed the measurement methods and precision of the inertial measurement unit sensor. The inertial measurement unit sensor is mounted on the end-effector of modular manipulator, to get the real-time pose of the end-effector. At last, a new inertial measurement unit-based iterative pose compensation algorithm is proposed. By applying this algorithm in the pose compensation experiment of modular manipulator which is composed of low-cost rotation joints, the results show that the inertial measurement unit can obtain a higher precision when in static state; it will accurately feedback to the control system with an accurate error compensation angle after a brief delay when the end-effector moves to the target point, and after compensation, the precision errors of roll angle, pitch angle, and yaw angle are reached at 0.05°, 0.01°, and 0.27°respectively. It proves that this low-cost method provides a new solution to improve the end-effector pose of low-cost modular manipulator.

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Joint axis and position estimation from inertial measurement data by exploiting kinematic constraints

Cited by 117 publications

References 7 publications

Experimental evaluation of joint position estimation using inertial sensors

Experimental evaluation of joint position estimation using inertial sensors

A Mobile Gait Analysis System for Optimization of Prosthetic Alignments

Inertial measurement unit–based iterative pose compensation algorithm for low-cost modular manipulator

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