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Optimized Trajectory Planning of Pick and Place Operations to Be Performed by Cable-Driven Parallel Robots

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Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 47))

Abstract

Cable driven parallel robots (CDPRs) have large workspace and versatile layouts which make them an interesting solution for high speed manipulation tasks. On the other hand, the available wrench set varies widely among the workspace, thus hardly affecting the performance of the system. For this reason, trajectory planning is a crucial aspect in CDPRs, and motion performance can be optimized only by considering the variability of wrench all along the path. In this paper, an optimized trajectory planning algorithm for CDPRs is proposed, which implements a pick and place task in the operational space. The algorithm, based on the calculation of the effective wrench capabilities of the robot in a set of control points along the path, allows to find the trajectory with the optimal trade-off between movement time and smoothness. The algorithm was tested in the case of an under-constrained suspended CDPR with 3-DOF and 4 cables conceived for pick and place applications. Results show that the optimal trajectory allows the CDPR to achieve values of acceleration and velocity near to the maximum allowable values defined by the polytopes of the CDPR.

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Acknowledgments

This work was supported by the Italian Ministry of University and Research (MIUR), call PRIN 2012, grant no. 20124SMZ88.

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Correspondence to Giulio Rosati .

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Barbazza, L., Oscari, F., Minto, S., Rosati, G. (2017). Optimized Trajectory Planning of Pick and Place Operations to Be Performed by Cable-Driven Parallel Robots. In: Boschetti, G., Gasparetto, A. (eds) Advances in Italian Mechanism Science. Mechanisms and Machine Science, vol 47. Springer, Cham. https://doi.org/10.1007/978-3-319-48375-7_31

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  • DOI: https://doi.org/10.1007/978-3-319-48375-7_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48374-0

  • Online ISBN: 978-3-319-48375-7

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