Six-DoF Pose Estimation for a Tendon-Driven Continuum Mechanism Without a Deformation Model

Deutschmann, Bastian; Chalon, Maxime; Reinecke, Jens; Maier, Maximilian; Ott, Christian

doi:10.1109/lra.2019.2927943

Cited by 11 publications

(10 citation statements)

References 28 publications

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“…For state estimation, the concept proposed by Deutschmann et al 42 is used, which performs a nonlinear least square minimization of a pose dependent error function. For the corresponding velocities, the numerical derivative of the estimated pose is computed as the solution of the optimization problem and generates smooth pose estimates.…”

Section: Methodsmentioning

confidence: 99%

Multi-input multi-output fractional-order control of an underactuated continuum mechanism

Deutschmann

Monje

Ott

2020

International Journal of Advanced Robotic Systems

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This article treats the design and implementation of a multi-input multi-output fractional-order controller for a nonlinear system composed of a tendon-driven continuum mechanism. As the continuum can be deformed along all Cartesian directions, it is suitable for the application as a flexible neck of a humanoid robot. In this work, a model-based control approach is proposed to control the position of the head, that is, the rigid body attached to the top of the continuum mechanism. Herein, the system is modeled as a rigid body on top of a nonlinear Cartesian spring, with an experimentally obtained deflection characteristic which provides a simple and real-time capable model. By nonlinear feedback, the output dynamics are linearized and decoupled, which enables the design of single-input single-output fractional-order controllers for the regulation of each output independently. The design of a fractional-order [Formula: see text] controller is discussed to incorporate robustness and a fast transient response. The proposed control approach is tested in several experiments on the real system.

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Section: Methodsmentioning

confidence: 99%

Multi-input multi-output fractional-order control of an underactuated continuum mechanism

Deutschmann

Monje

Ott

2020

International Journal of Advanced Robotic Systems

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“…In a prior publication (Deutschmann et al, 2019), the estimation problem was solved using the geometric model for the length sensors of Eq. 5.…”

Section: Problem Statementmentioning

confidence: 99%

“…In tests on the real hardware, the pose could be predicted with a maximum estimation error of ± 4.5 mm for position and ±4°o rientation (Deutschmann et al, 2019). The drawbacks of this method are that a good initial estimate is required to converge, the presence of local minima, and the assumption of perfectly known dimensions, e.g., the location of the pulleys and hinges w.r.t.…”

Section: Problem Statementmentioning

confidence: 99%

Fault-Tolerant Six-DoF Pose Estimation for Tendon-Driven Continuum Mechanisms

2021

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We propose a fault-tolerant estimation technique for the six-DoF pose of a tendon-driven continuum mechanisms using machine learning. In contrast to previous estimation techniques, no deformation model is required, and the pose prediction is rather performed with polynomial regression. As only a few datapoints are required for the regression, several estimators are trained with structured occlusions of the available sensor information, and clustered into ensembles based on the available sensors. By computing the variance of one ensemble, the uncertainty in the prediction is monitored and, if the variance is above a threshold, sensor loss is detected and handled. Experiments on the humanoid neck of the DLR robot DAVID, demonstrate that the accuracy of the predicted pose is significantly improved, and a reliable prediction can still be performed using only 3 out of 8 sensors.

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“…While there are different approaches for the actuation of CRs, tendon-driven actuation has become popular owing to its simplicity and ease of implementation [13]. As a result, various aspects related to tendon-driven continuum robots have been the subject of investigation, such as their design and construction [14], [15], mechanical modeling [16]- [19], dynamics [20], [21], workspace analysis [22], [23], and control [24]. Despite these advances, dynamic modeling and analysis of tendon-driven continuum robots present significant challenges, such as those relating to their accuracy [25], efficiency, and numerical stability.…”

Section: Introductionmentioning

confidence: 99%

Cosserat Rod-Based Dynamic Modeling of Tendon-Driven Continuum Robots: A Tutorial

2021

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This article provides a tutorial on the dynamic modeling of continuum robots. Continuum robots (CRs) have gained popularity in recent years due to their flexible backbone structure. Modeling and control of CRs motivate accurate and efficient dynamic models. Such models will enable simulation of dynamic behavior, improved structural design, and the development of dynamics-based control systems for CRs. As a unified underlying approach, the Cosserat rod-based modeling of tendon-driven CRs is used as the basis of the modeling techniques discussed in this paper. In addition to conventional continuum robot assemblies, new and emerging assemblies such as tendon-bent concentric tube and co-operative robots are also considered. The governing equations of motion for conventional CRs are first summarized and then extended for other tendon-driven CRs. This tutorial also contributes to developing a MATLAB code package for simulation of the dynamic response of these robots. The presented method and codes provide a useful and compact resource for readers and can be used for further development of tendon-driven continuum robots.

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Six-DoF Pose Estimation for a Tendon-Driven Continuum Mechanism Without a Deformation Model

Cited by 11 publications

References 28 publications

Multi-input multi-output fractional-order control of an underactuated continuum mechanism

Multi-input multi-output fractional-order control of an underactuated continuum mechanism

Fault-Tolerant Six-DoF Pose Estimation for Tendon-Driven Continuum Mechanisms

Cosserat Rod-Based Dynamic Modeling of Tendon-Driven Continuum Robots: A Tutorial

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