Evidence map›Paper›PMID 32031916›Full record

ArticleSoft robotics2020

Rolling Locomotion of Cable-Driven Soft Spherical Tensegrity Robots.

Kyunam Kim, Adrian K Agogino, Alice M Agogino

Abstract read
In one paragraph

Article in Soft robotics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Legged Robot with Tensegrity Feature Bionic Knee Joint.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
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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

3 authors.

Kyunam KimDepartment of Aerospace, California Institute of Technology, Pasadena, California.
Adrian K AgoginoNASA Ames Research Center, Moffett Field, California.
Alice M AgoginoDepartment of Mechanical Engineering, University of California at Berkeley, Berkeley, California.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soft spherical tensegrity robots are novel steerable mobile robotic platforms that are compliant, lightweight, and robust. The geometry of these robots is suitable for rolling locomotion, and they achieve this motion by properly deforming their structures using carefully chosen actuation strategies. The objective of this work is to consolidate and add to our research to date on methods for realizing rolling locomotion of spherical tensegrity robots. To predict the deformation of tensegrity structures when their member forces are varied, we introduce a modified version of the dynamic relaxation technique and apply it to our tensegrity robots. In addition, we present two techniques to find desirable deformations and actuation strategies that would result in robust rolling locomotion of the robots. The first one relies on the greedy search that can quickly find solutions, and the second one uses a multigeneration Monte Carlo method that can find suboptimal solutions with a higher quality. The methods are illustrated and validated both in simulation and with our hardware robots, which show that our methods are viable means of realizing robust and steerable rolling locomotion of spherical tensegrity robots.

Indexed as

RoboticsComputersComputer SimulationLocomotionMotiondynamic relaxationgreedy searchmultigeneration Monte Carlotensegrity robots

Identifiers

PMID32031916
PMCPMC7301328

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.