Evidence map›Paper›PMID 36105760›Full record

ArticleFrontiers in robotics and AI2022

Variable stiffness locomotion with guaranteed stability for quadruped robots traversing uneven terrains.

Xinyuan Zhao, Yuqiang Wu, Yangwei You, Arturo Laurenzi, Nikos Tsagarakis

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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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

2 citing papers in PubMed.

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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.

Xinyuan ZhaoHumanoid and Human Centered Mechatronics Research Line, Istituto Italiano di Tecnologia, Genova, Italy.
Yuqiang WuCorporate Research Center, Mechatronics Research Institute, Midea Group Co., Ltd., Foshan, China.
Yangwei YouXiaomi, Beijing, China.
Arturo LaurenziHumanoid and Human Centered Mechatronics Research Line, Istituto Italiano di Tecnologia, Genova, Italy.
Nikos TsagarakisHumanoid and Human Centered Mechatronics Research Line, Istituto Italiano di Tecnologia, Genova, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quadruped robots are widely applied in real-world environments where they have to face the challenges of walking on unknown rough terrains. This paper presents a control pipeline that generates robust and compliant legged locomotion for torque-controlled quadruped robots on uneven terrains. The Cartesian motion planner is designed to be reactive to unexpected early and late contacts using the estimated contact forces. Moreover, we present a novel scheme of optimal stiffness modulation that aims to coordinate desired compliance and tracking performance. It optimizes joint stiffness and contact forces coordinately in a quadratic programming (QP) formulation, where the constraints of non-slipping contacts and torque limits are imposed as well. In addition, the issue of stability under variable stiffness control is solved by imposing a tank-based passivity constraint explicitly. We finally validate the proposed control pipeline on our quadruped robot CENTAURO in experiments on uneven terrains and, through comparative tests, demonstrate the improvements of the variable stiffness locomotion.

Indexed as

contact force optimizationlocomotion controlquadruped robotstouchdown adaptationvariable stiffness control

Identifiers

PMID36105760
PMCPMC9465384

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.