Evidence map›Paper›PMID 36091418›Full record

ArticleFrontiers in neurorobotics2022

Exploring the effects of serial and parallel elasticity on a hopping robot.

Guoping Zhao, Omid Mohseni, Marc Murcia, Andre Seyfarth, Maziar A Sharbafi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurorobotics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Guoping ZhaoLauflabor Locomotion Laboratory, Centre for Cognitive Science, Technical University of Darmstadt, Darmstadt, Germany.
Omid MohseniLauflabor Locomotion Laboratory, Centre for Cognitive Science, Technical University of Darmstadt, Darmstadt, Germany.
Marc MurciaLauflabor Locomotion Laboratory, Centre for Cognitive Science, Technical University of Darmstadt, Darmstadt, Germany.
Andre SeyfarthLauflabor Locomotion Laboratory, Centre for Cognitive Science, Technical University of Darmstadt, Darmstadt, Germany.
Maziar A SharbafiLauflabor Locomotion Laboratory, Centre for Cognitive Science, Technical University of Darmstadt, Darmstadt, Germany.
Technical University of Darmstadt · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The interaction between the motor control and the morphological design of the human leg is critical for generating efficient and robust locomotion. In this paper, we focus on exploring the effects of the serial and parallel elasticity on hopping with a two-segmented robotic leg called electric-pneumatic actuation (EPA)-Hopper. EPA-Hopper uses a hybrid actuation system that combines electric motors and pneumatic artificial muscles (PAM). It provides direct access to adjust the physical compliance of the actuation system by tuning PAM pressures. We evaluate the role of the serial and parallel PAMs with different levels of compliance with respect to four criteria: efficiency, performance, stability, and robustness of hopping against perturbations. The results show that the serial PAM has a more pronounced impact than the parallel PAM on these criteria. Increasing the stiffness of the serial PAM decreases the leg stiffness of the unloading phase during hopping. The stiffer the leg, the more efficient and the less robust the movement. These findings can help us further understand the human hopping mechanism and support the design and control of legged robots and assistive devices.

Indexed as

hopping robothybrid actuationparallel elasticitypneumatic artificial muscleserial elasticity

Identifiers

PMID36091418
PMCPMC9449899
OpenAlexW4293113450

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.