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Optimizing the Topology of Tendon-Driven Fingers: Rationale, Predictions and Implementation

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The Human Hand as an Inspiration for Robot Hand Development

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 95))

Abstract

Tendon-driven mechanisms in general, and tendon-driven fingers in particular, are ubiquitous in nature, and are an important class of bio-inspired mechatronic systems. However, the mechanical complexity of tendon-driven systems has hindered our understanding of biological systems and the optimization of the design, performance, control, and construction of mechatronic systems. Here we apply our recently-developed analytical approach to tendon-driven systems [1] to describe a novel, systematic approach to analyze and optimize the routing of tendons for force-production capabilities of a reconfigurable 3D tendon-driven finger. Our results show that these capabilities could be increased by up to 277 % by rerouting tendons and up to 82 % by changing specific pulley sizes for specific routings. In addition, we validate these large gains in performance experimentally. The experimental results for 6 implemented tendon routings correlated very highly with theoretical predictions with an \( R^{2} \) value of 0.987, and the average effect of unmodeled friction decreased performance an average of 12 %. We not only show that, as expected, functional performance can be highly sensitive to tendon routing and pulley size, but also that informed design of fingers with fewer tendons can exceed the performance of some fingers with more tendons. This now enables the systematic simplification and/or optimization of the design and construction of novel robotic/prosthetic fingers. Lastly, this design and analysis approach can now be used to model complex biological systems such as the human hand to understand the synergistic nature of anatomical structure and neural control.

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Notes

  1. 1.

    The sum of maximal tendon tensions being equal is an important constraint due to the size, weight, and motor torque (and therefore tendon tension) limitations inherent in dexterous hands. For example, the torque capacity of motors is roughly proportional to motor weight, and minimization of weight was an important consideration in the design of the DLR Hand II [44]. In addition, the maximal force production capabilities of McKibben-style muscles are roughly proportional to cross-sectional area [45]. Since the actuators typically will be located in the forearm, then the total cross-sectional area will be limited to the forearm cross-sectional area. In this study, for simplicity and without affecting the generalizability of our approach or results, we do not consider alternative constraints on the actuation system (e.g., electrical current capacity, tendon velocities, etc).

  2. 2.

    Due to the nature of our full combinatoric search, moment arm matrices that produced mirrored feasible force sets about a plane passing through the origin (which would have the same MIV) were discarded and also those moment arm matrices that were produced by a rearrangement of the columns. For example, in Fig. 4, interchanging columns 5 and 6 does not change the feasible force set, it only reverses the “numbering” of the tendons. But in the full combinatoric search, both of these numberings would be different matrices producing identical feasible force sets.

  3. 3.

    Take an extreme case in which friction loss was 50 % exactly for every tendon. The theoretical feasible force set is a unit cube. While the shape of the experimental feasible force set would be also an exact cube, it would be 50 % contracted in every direction and therefore the corresponding vertices would be far from each other. If we normalized the volume, the corresponding vertices would be in the same location, and the mean distance (in shape similarity) would be zero.

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Acknowledgments

The authors gratefully acknowledge the help of Dr. Manish Kurse in providing the data acquisition routine for the experimental procedure, and Dr. Veronica Santos for construction of the gimbal used in the experiments.

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Correspondence to Francisco J. Valero-Cuevas .

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Inouye, J.M., Kutch, J.J., Valero-Cuevas, F.J. (2014). Optimizing the Topology of Tendon-Driven Fingers: Rationale, Predictions and Implementation. In: Balasubramanian, R., Santos, V. (eds) The Human Hand as an Inspiration for Robot Hand Development. Springer Tracts in Advanced Robotics, vol 95. Springer, Cham. https://doi.org/10.1007/978-3-319-03017-3_12

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