Evidence map›Paper›PMID 40287513›Full record

ArticleCommunications engineering2025

Spatially distributed biomimetic compliance enables robust anthropomorphic robotic manipulation.

Kai Junge, Josie Hughes

Abstract read
In one paragraph

Article in Communications engineering, 2025. 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

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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Kai JungeCREATE Lab, EPFL, Lausanne, Switzerland. kai.junge@epfl.ch.ORCID http://orcid.org/0000-0002-5274-9561
Josie HughesCREATE Lab, EPFL, Lausanne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The impressive capabilities of humans to robustly perform manipulation stems from compliant interactions, enabled by the structure and materials distributed in the hands. We propose that mimicking this spatially distributed compliance in an anthropomorphic robotic hand enhances open-loop manipulation robustness and leads to human-like behaviors. Here we introduce the ADAPT Hand, equipped with configurable compliant elements on the skin, fingers, and wrist. After quantifying the effect of compliance on individual components against a rigid configuration, we experimentally analyze the performance of the full hand. Through automated pick-and-place tests, we show the grasping robustness mirrors the estimated geometric theoretical limit, while stress-testing the robot to perform 800+ grasps. Finally, 24 items with varying geometries are grasped in a constrained environment with a 93% success rate. We demonstrate that the hand-object self-organization behavior, driven by passive adaptation, underpins this robustness. The hand exhibits different grasp types based on object geometries, with a 68% similarity to natural human grasps.

Identifiers

PMID40287513
PMCPMC12033370

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.