Manipulability index study on the KUKA robot KR5 ARC HW

Henao, Juan Camilo Ramírez; Garzon, Jorge Alberto Jaramillo; Mumoz, Leonardo Duque

doi:10.1109/stsiva.2012.6340560

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…In the case of complex robotic tasks, where simultaneous tracking of the tool tip along the surface of the workpiece at a constant tool speed is required, such as milling [7,8], welding [9], composite laying [10,11] or hammer peening, it is not always necessary that such a task will be feasible with the required technological parameters for arbitrary workpiece placement in the robot's workspace. The available motion capabilities are reduced significantly if we compare collaborative robots to traditional industrial robots, due to the size of the integrated actuators [6].…”

Section: Introductionmentioning

confidence: 99%

Workpiece Placement Optimization for Robot Machining Based on the Evaluation of Feasible Kinematic Directional Capabilities

Stradovnik,

Hace

2024

Applied Sciences

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Workpiece placement plays a crucial role when performing complex surface machining task robotically. If the feasibility of a robotic task needs to be guaranteed, the maximum available capabilities should be higher than the joint capabilities required for task execution. This can be challenging, especially when performing a complex surface machining task with a collaborative robot, which tend to have lower motion capabilities than conventional industrial robots. Therefore, the kinematic and dynamic capabilities within the robot workspace should be evaluated prior to task execution and optimized considering specific task requirements. In order to estimate maximum directional kinematic capabilities considering the requirements of the surface machining task in a physically consistent and accurate way, the Decomposed Twist Feasibility (DTF) method will be used in this paper. Estimation of the total kinematic performance capabilities can be determined accurately and simply using this method, adjusted specifically for robotic surface machining purposes. In this study, we present the numerical results that prove the effectiveness of the DTF method in identifying the optimal placement of predetermined machining tasks within the robot’s workspace that requires lowest possible joint velocities for task execution. These findings highlight the practicality of the DTF method in enhancing the feasibility of complex robotic surface machining operations.

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Section: Introductionmentioning

confidence: 99%

Workpiece Placement Optimization for Robot Machining Based on the Evaluation of Feasible Kinematic Directional Capabilities

Stradovnik,

Hace

2024

Applied Sciences

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Optimización de manipulabilidad y consumo eléctrico mediante el Algoritmo Heurístico de Kalman en manipuladores seriales

Henao

Duque-Muñoz

2015

ing.cienc.

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En el presente trabajo se plantea una metodología de planeación de trayectorias para manipuladores seriales antropomórficos de seis grados de libertad y muñeca esférica enfocada en la minimización del consumo eléctrico y maximización de la manipulabilidad. Para lograr tal fin se expone un algoritmo de optimización el cual tiene como base el Algoritmo Heurístico de Kalman (AHK), cuya finalidad es encontrar la trayectoria óptima según la función multi-objetivo propuesta dentro de un espacio esférico simplificado propuesto. El algoritmo de optimización se evalúa mediante el análisis del comportamiento de dos trayectorias en el manipulador PUMA 560, simuladas en un programa desarrollado en la aplicación de Visual Basic perteneciente al software Autodesk Inventor.

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Task-Oriented Evaluation of the Feasible Kinematic Directional Capabilities for Robot Machining

Stradovnik

Hace

2022

Sensors

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Performing the machining of complex surfaces can be a challenging task for a robot, especially in terms of collaborative robotics, where the available motion capabilities are greatly reduced in comparison with conventional industrial robot arms. It is necessary to evaluate these capabilities prior to task execution, for which we need efficient algorithms, especially in the case of flexible robot applications. To provide accurate and physically consistent information about the maximum kinematic capabilities while considering the requirements of the task, an approach called the Decomposed Twist Feasibility (DTF) method is proposed in this study. The evaluation of the maximum feasible end-effector velocity is based on the idea of decomposition into the linear and angular motion capabilities, considering a typical robot machining task with synchronous linear and angular motion. The proposed DTF method is presented by the well-known manipulability polytope concept. Unlike the existing methods that estimate the kinematic performance capabilities in arbitrarily weighted twist space, or separately in the translation and the rotation subspace, our approach offers an accurate and simple solution for the determination of the total kinematic performance capabilities, which is often highly required, especially in the case of robot machining tasks. The numerical results obtained in this study show the effectiveness of the proposed approach. Moreover, the proposed DTF method could represent suitable kinematic performance criteria for the optimal placement of predefined tasks within the robot workspace.

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Manipulability index study on the KUKA robot KR5 ARC HW

Cited by 3 publications

References 9 publications

Workpiece Placement Optimization for Robot Machining Based on the Evaluation of Feasible Kinematic Directional Capabilities

Workpiece Placement Optimization for Robot Machining Based on the Evaluation of Feasible Kinematic Directional Capabilities

Optimización de manipulabilidad y consumo eléctrico mediante el Algoritmo Heurístico de Kalman en manipuladores seriales

Task-Oriented Evaluation of the Feasible Kinematic Directional Capabilities for Robot Machining

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