Tendon-driven robot

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Tendon-driven robots (TDR) are robots whose limbs mimic biological musculoskeletal systems. They use plastic straps to mimic muscles and tendons. Such robots are claimed to move in a "more natural" way than traditional robots that use rigid metal or plastic limbs controlled by geared actuators. TDRs can also help understand how biomechanics relates to embodied intelligence and cognition.[1]

Challenges include effectively modeling the human body’s complex motions and ensuring accurate positioning, given that the tendons are prone to stretch, which costs them strength and smooth operation.[1]

Existing systems[]

TDRs are the subject of considerable research and commercial systems followed.

Myorobotics[]

Myorobotics is a toolkit comprising muscles, tendons, joints, and bones to build diverse tendon-driven musculoskeletal robots, e.g. anthropomimetic arms with complex shoulder joints, quadrupeds, and hopping robots. Robots can be assembled, optimized, and simulated from primitives, then built and controlled either from the same software or from brain-like spiking neural networks simulated on a neuromorphic computer.[2]

Roboy[]

Main article: ROBOY

Roboy is four feet tall and has two tendon-driven arms. Researchers announced plans to make Roboy’s design open-source, allowing anyone with a 3-D printer to build and tinker with their own version.[3]

Kenshiro[]

Kenshiro is a University of Tokyo robot announced in 2012. Kenshiro is somewhat larger than Roboy and includes 160 pulley-like muscles and aluminum bones that allow it to perform simple bends and poses. [4]

BioRob[]

Bionic Robotics offered BioRob, a tendon-driven robotic arm for industrial use. It has a flexible mechanical structure that allows it to pick up heavy payloads even though it weighs much less than the conventional robotic arm that the company also makes. BioRob’s light weight and flexible design is claimed to offer greater safety for use around human workers.

Caliper[]

Caliper is a framework for the simulation of tendon-driven robots. It consists of a generic capable of utilizing computer-aided design models and tools for simulation control, data acquisition and system investigation.[5]

ACT Hand[]

The Anatomically Correct Testbed robotic hand [6] uses tendons and woven finger extensor hoods to capture the biomechanical properties of the human hand. The tendons slide over 3D printed bones matching human bone shapes, reproducing the variable moment arms and some of the tendon network interactions found in the human hand. The tendons are actuated by direct drive (without gearing), allowing them to spool out freely when other tendons oppose them in the skeleton.[7]

See also[]

References[]

  1. ^ a b Hope, Aviva (2013-09-27). "Some Robots Are Starting to Move More Like Humans | MIT Technology Review". Technologyreview.com. Retrieved 2013-10-07.
  2. ^ Richter, C.; Jentzsch, S.; Hostettler, R.; Garrido, J. A.; Ros, E.; Knoll, A.; Rohrbein, F.; Smagt, P. van der; Conradt, J. (December 2016). "Musculoskeletal Robots: Scalability in Neural Control". IEEE Robotics Automation Magazine. 23 (4): 128–137. arXiv:1601.04862. doi:10.1109/MRA.2016.2535081. ISSN 1070-9932.
  3. ^ ROBOY video on YouTube
  4. ^ Kozuki, T.; Mizoguchi, H.; Asano, Y.; Osada, M.; Shirai, T.; Junichi, U.; Nakanishi, Y.; Okada, K.; Inaba, M. (October 2012). "Design methodology for the thorax and shoulder of human mimetic musculoskeletal humanoid Kenshiro -a thorax structure with rib like surface -". 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. pp. 3687–3692. doi:10.1109/IROS.2012.6386166.
  5. ^ Wittmeier, S.; Jantsch, M.; Dalamagkidis, K.; Rickert, M.; Marques, H. G.; Knoll, A. (2011). "CALIPER: A universal robot simulation framework for tendon-driven robots". 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (PDF). p. 1063. doi:10.1109/IROS.2011.6094455. ISBN 978-1-61284-456-5.
  6. ^ "Rombokas, Eric, et al. "Tendon-Driven Variable Impedance Control Using Reinforcement Learning." Robotics Science and Systems (2013): 369" (PDF).
  7. ^ "University of Texas at Austin, ReNeu Robotics Lab".

External links[]

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