Investigation of reliability of hydraulic-robots for hazardous environments using analytic redundancy

Leuschen, Martin L.; Walker, Ian D.; Cavallaro, Joseph R.

doi:10.1109/rams.1999.744107

Cited by 13 publications

(16 citation statements)

References 7 publications

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“…These allow to be expressed in coordinate-free form as (14) using the identity with (4). This used in (7) allows calculation of (6) with no online integration.…”

Section: A Calculating For Rotational Jointmentioning

confidence: 99%

“…This used in (7) allows calculation of (6) with no online integration. Equation (14) can be efficiently calculated in frame .…”

Section: A Calculating For Rotational Jointmentioning

confidence: 99%

“…When joint is rotational, applying the product rule to (14) and using the fact that outboard, fixed-length vectors move according to the rule , gives…”

Section: ) Joint Rotationalmentioning

confidence: 99%

“…Using (7) in (22) and factoring out gives (23) Now, if is defined as (24) where is the cross-product matrix for and is the cross-product matrix for , and is defined as (25) then, using (14), (23) becomes (26) The matrix as defined through (24) and (25) is analogous to the second moment of composite rigid-body inertia [30]; it can be calculated through the following procedure. Let the net outboard interest parameter be , calculated using (27) And let be the outboard interest vector, calculated using (28) where for calculation, and are both expressed in D-H frame .…”

Section: A Calculating For Rotational Jointmentioning

confidence: 99%

“…The aim is to achieve a degree of failure tolerance by either best configuring a manipulator in anticipation of a failure or reconfiguring it for failure recovery, possibly in conjunction with other recovery methods [9]. Failure tolerance is especially important for manipulators used in hazardous or remote environments [10]- [14], and kinematically redundant manipulators have been proposed for use there [2], [15]- [21].…”

Section: Introductionmentioning

confidence: 99%

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Measuring and reducing the Euclidean-space effects of robotic joint failures

English¹,

Maciejewski

2000

IEEE Trans. Robot. Automat.

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Abstract-Robotic joint failures are directly characterized and measured in joint space. A locking failure, for example, is one for which a joint cannot move, and it gives an error equal to the desired value minus the locked value. This article extends the joint-space characterization to Euclidean space by measuring a failure's effect there. The approach is based on a rudimentary measure of point error that can be defined to be distance or path length. It is used to form comprehensive measures through weighted integration over Euclidean-space regions. For kinematically redundant manipulators, minimizing the measures using the redundancy is a method to induce failure tolerance. This can be applied both before a failure to reduce the likelihood of collision-induced damage and after a failure to reduce end-effector error. Examples for both cases are given.

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“…These allow to be expressed in coordinate-free form as (14) using the identity with (4). This used in (7) allows calculation of (6) with no online integration.…”

Section: A Calculating For Rotational Jointmentioning

confidence: 99%

“…This used in (7) allows calculation of (6) with no online integration. Equation (14) can be efficiently calculated in frame .…”

Section: A Calculating For Rotational Jointmentioning

confidence: 99%

“…When joint is rotational, applying the product rule to (14) and using the fact that outboard, fixed-length vectors move according to the rule , gives…”

Section: ) Joint Rotationalmentioning

confidence: 99%

Section: A Calculating For Rotational Jointmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Measuring and reducing the Euclidean-space effects of robotic joint failures

English¹,

Maciejewski

2000

IEEE Trans. Robot. Automat.

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Nonlinear Fault Detection for Hydraulic Systems

Leuschen¹,

Walker²,

Cavallaro³

Springer Tracts in Advanced Robotics

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Abstract. One of the most important areas in the robotics industry is the development of robots capable of working in hazardous environments. As humans cannot safely or cheaply work in these environments, providing a high level of robotic functionality is important. Our work in this area focuses on a fault detection method known as analytical redundancy, or AR. In this paper we discuss the application to a hydraulic servovalve system of our novel rigorous nonlinear AR technique. AR is a model-based state-space technique that is theoretically guaranteed to derive the maximum number of independent tests of the consistency of sensor data with the system model and past control inputs. Conventional linear AR is only valid for linear sampled data systems. However, our new nonlinear AR (NLAR) technique maintains traditional linear AR's mathematical guarantee to generate the maximum possible number of independent tests in the nonlinear domain. Thus NLAR allows us to gain the benefits of AR testing for nonlinear systems with both continuous and sampled data.

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Identification schemes for unmanned excavator arm parameters

Zweiri

2008

Int. J. Autom. Comput.

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Parameter identification is a key requirement in the field of automated control of unmanned excavators (UEs). Furthermore, the UE operates in unstructured, often hazardous environments, and requires a robust parameter identification scheme for field applications. This paper presents the results of a research study on parameter identification for UE. Three identification methods, the Newton-Raphson method, the generalized Newton method, and the least squares method are used and compared for prediction accuracy, robustness to noise and computational speed. The techniques are used to identify the link parameters (mass, inertia, and length) and friction coefficients of the full-scale UE. Using experimental data from a full-scale field UE, the values of link parameters and the friction coefficient are identified. Some of the identified parameters are compared with measured physical values. Furthermore, the joint torques and positions computed by the proposed model using the identified parameters are validated against measured data. The comparison shows that both the Newton-Raphson method and the generalized Newton method are better in terms of prediction accuracy. The Newton-Raphson method is computationally efficient and has potential for real time application, but the generalized Newton method is slightly more robust to measurement noise. The experimental data were obtained in collaboration with QinetiQ Ltd.

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Investigation of reliability of hydraulic-robots for hazardous environments using analytic redundancy

Cited by 13 publications

References 7 publications

Measuring and reducing the Euclidean-space effects of robotic joint failures

Measuring and reducing the Euclidean-space effects of robotic joint failures

Nonlinear Fault Detection for Hydraulic Systems

Identification schemes for unmanned excavator arm parameters

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