Automatic reconfiguration of a robotic arm using a multi-agent approach

Britain, S L; Gibb, Alex; Roberts, Clive

doi:10.1243/09596518jsce335

Cited by 5 publications

(4 citation statements)

References 14 publications

(11 reference statements)

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“…Inverse kinematics is an analysis method that joint angles can be solved with known position and orientation of the end-effector. Suppose the position and orientation vector of the end-effector is q = ½n x , n y , n z , o x , o y , o z , a x , a y , a z , p x , p y , p z T 2 R 12 3 1 , where p x , p y , p z are the position parameters along X, Y, and Z axis, then n x , n y , n z , o x , o y , o z , a x , a y , a z are the orientation parameters respectively 28 q is determined by the six variables p x , p y , p z, a, b, g. Suppose the measured position and orientation vector in the robot system (or converted in the robot system) is q m , target position and orientation vector in the robot system (or converted in the robot system) is q t . The actual and theoretical forward kinematic operators are respectively…”

Section: Modeling Of the Position Error And Compensated Joint Angle I...mentioning

confidence: 99%

A positioning error compensation method for multiple degrees of freedom robot arm based on the measured and target position error

Feng

Ouyang

et al. 2022

Advances in Mechanical Engineering

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A novel positioning error compensation method (PECM) based on the measured and target position error for multiple degrees of freedom (DOF) robot arm control is proposed, which is used to improve positioning accuracy of multiple-DOF robot arm end-effector in accurate positioning applications such as in the medical and mechanical fields. Based on the idea of PID to increase adaptiveness and robustness of the method, a positioning compensation model between the measured and target position error tracked by an optical tracking system and compensated joint angle is derived with inverse kinematic model. Based on error analysis of the compensation model regarding geometry errors, the proportional joint angle compensated coefficient deduced from Jaccobian matrix of the error is proposed and identified with position error data. Calibration experiments for position conversion matrix and positioning accuracy verification experiments are conducted consisting of an optical tracking system and a robot arm. The results of positioning accuracy verification experiments show that the average resultant positioning error in three directions reduces from 1.89 mm (before compensation, model based on Denavit-Hartenberg (DH)), 0.39 mm (model based on modified Denavit-Hartenberg (MDH) with Levenberg-Marquardt (LM)) to 0.34 mm (decreasing 82%, 15%), which demonstrates the efficiency and robustness of the method.

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Section: Modeling Of the Position Error And Compensated Joint Angle I...mentioning

confidence: 99%

A positioning error compensation method for multiple degrees of freedom robot arm based on the measured and target position error

Feng

Ouyang

et al. 2022

Advances in Mechanical Engineering

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“…we discard assumption A.7. The resulting transition probability function is presented in Equation (13). Note that although the probabilities of each transition type are shown separately, any combination of the transitions can happen in any state.…”

Section: Mdp Formulationmentioning

confidence: 99%

A Mission Based Fault Reconfiguration Framework for Spacecraft Applications

Nasir

Atkins

Kolmanovsky

2012

Infotech@Aerospace 2012

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We present a Markov Decision Process (MDP) framework for computing post-fault reconfiguration policies that are optimal with respect to a discounted cost. Our cost function penalizes states that are unsuitable to achieve the remaining objectives of the given mission. The cost function also penalizes states where the necessary goal achievement actions cannot be executed. We incorporate probabilities of missed detections and false alarms for a given fault condition into our cost to encourage the selection of policies that minimize the likelihood of incorrect reconfiguration. To illustrate the implementation of our proposed framework, we present an example inspired by the Far Ultraviolet Spectroscopic Explorer (FUSE) spacecraft with a mission to collect scientific data from 5 targets. Using this example, we also demonstrate that there is a design tradeoff between safe operation and mission completion. Simulation results are presented to illustrate and manage this tradeoff through the selection of optimization parameters.

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“…This is a methodology that is applicable to any robotic configuration with a serial, parallel, or hybrid structure, but a unique model formulation must be developed and solved for each configuration. A novel, adaptive approach based on multiagent systems was developed by [4] for solving inverse kinematic equations using a collaborative agent based approach to reduce the problem complexity, but no distinct formulation is presented that can be extended to develop a dynamic model and a control strategy. Symbolic computation of manipulator inverse kinematics using the homogeneous transformation matrices and the product of the exponential formulas are presented by [24], but this model is not comprehensive.…”

Section: Dof Planar Robotmentioning

confidence: 99%

“…Combining Eqs (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18), the solution for the inverse kinematics is expressed in the following two equations: …”

Section: Inverse Kinematic Solution For the Planar 2 Dof Reconfigurabmentioning

confidence: 99%

Design and evaluation of reconfigurable robotic systems for 2 1/2 axis based material deposition strategies

Djuric

Urbanic

2009

ICA

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Simulation tools need to be developed to support modeling and product/process analysis activities for material deposition processes. The long term research goal is to develop a set of virtual modeling tools to support advanced tool motions and process planning strategies for this application. The goal of this research is to develop a reconfigurable robotic platform that can adapt alternative deposition strategies while respecting the unique process-related constraints for 2 1 /2 axis and 2 1 /2 axis + 2 axis tool paths. A variety of topologies are investigated. For the selected systems, a parametric kinematic, dynamic and control model is developed, and results presented for kinematic and dynamic reconfigurations. An adaptability assessment is performed to determine a relative effort measure to physically reconfigure a base platform to a potential new configuration. This combined with reviewing the modeling complexity issue, is used to determine an appropriate base platform. To simulate the process realistically using existing tools, a methodology is developed to illustrate material deposition in conjunction with the tool motions for the systems investigated.

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Automatic reconfiguration of a robotic arm using a multi-agent approach

Cited by 5 publications

References 14 publications

A positioning error compensation method for multiple degrees of freedom robot arm based on the measured and target position error

A positioning error compensation method for multiple degrees of freedom robot arm based on the measured and target position error

A Mission Based Fault Reconfiguration Framework for Spacecraft Applications

Design and evaluation of reconfigurable robotic systems for 2 1/2 axis based material deposition strategies

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