Evidence map›Paper›PMID 40267192›Full record

ArticleScience advances2025

Encoding mechanical intelligence using ultraprogrammable joints.

Rui Wu, Luca Girardi, Stefano Mintchev

Abstract read
In one paragraph

Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Noncircular rolling contact joints enable programmed behavior in robotic linkages.Proceedings of the National Academy of Sciences of the United States of America · 2026
    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

3 authors.

Rui WuEnvironmental Robotics Laboratory, Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland.ORCID 0000-0001-8311-6014
Luca GirardiEnvironmental Robotics Laboratory, Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland.ORCID 0000-0002-9904-1157
Stefano MintchevEnvironmental Robotics Laboratory, Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Animal bodies act as physical controllers, with their finely tuned passive mechanical responses physically "encoding" complex movements and environmental interactions. This capability allows animals to perform challenging tasks with minimal muscular or neural activities, a phenomenon known as embodied intelligence. However, realizing such robots remains challenging due to the lack of mechanically intelligent bodies with abundant tunable parameters-such as tunable stiffness-which is a critical factor akin to the programmable parameters of a neural network. We introduce an elastic rolling cam (ERC) with accurately inverse-designable rotational stiffness. The ERC can closely replicate 100,000 randomly generated stiffness profiles in simulation. Prototypes ranging from millimeters to centimeters were manufactured. To illustrate the mechanical intelligence encoded by programming the ERC's stiffness response, we designed a bipedal robot with optimized ERC passive knees, achieving energy-efficient, open-loop stable walking across uneven terrain. We also demonstrated a quadcopter drone with ERC joints encoding an impact-activated, dual-state morphing.

Indexed as

Artificial IntelligenceJointsRoboticsAnimalsBiomechanical PhenomenaWalking

Identifiers

PMID40267192
PMCPMC12017317

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.