MétaCan
Menu
Back to cohort
Record W4402675186 · doi:10.1089/soro.2022.0214

Soft-Rigid Hybrid Revolute and Prismatic Joints Using Multilayered Bellow-Type Soft Pneumatic Actuators: Design, Characterization, and Its Application as Soft-Rigid Hybrid Gripper

2024· article· en· W4402675186 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSoft Robotics · 2024
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsActuatorPneumatic actuatorSoft roboticsRevolute jointMaterials scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Despite the exponentially expanding capabilities of robotic systems with the introduction of soft robotics, the lack of practical considerations in designing and integrating soft robotic components hinders the widespread application of newly developed technology in real life. This study investigates the development and performance evaluation of soft-rigid hybrid (SRH) robotic systems employing multilayered bellow-shaped soft pneumatic actuators (MBSPAs) to overcome the common challenges exclusively exhibited in soft robotics. Specifically, we introduce a unique SRH revolute joint enabled by a single thermoplastic polyurethane-MBSPA and rigid components to tackle the limitations of existing soft pneumatic actuators (SPAs), such as restricted payload capacity, vulnerability to external damages, and lack of resilience against outdoor environment. The proposed SRH system entails rigid components encapsulating to protect the MBSPA throughout the entirety of the desired range of motion, and demonstrates improved displacement efficiency, force output, and resilience against external loads. The rigid components also help to stabilize the axis of motion, fostering high durability and repeatable motion. We also extend this concept to a one-degree of freedom SRH prismatic joint. Finite element method modeling is used to estimate the general actuator performance, facilitating the design of MBSPA with limited material information and bypassing trial and error. The wider application of this research targets delicate object handling in industries such as agriculture, encouraging safe and efficient automated harvesting. The article includes thorough actuator performance characterization including displacement, frequency response, durability with life cycle testing up to 25,000 cycles, force output, stiffness, and power density. Performance comparisons with other SPA are provided. A proof of concept 3-point gripper enabled by the proposed SRH joints is capable of gripping objects of various sizes and shapes, with detailed workspace analysis and demonstration showing the gripper's versatility. The SRH system presented here lays a robust foundation for the ongoing advancement of soft robotic technology toward real-life applications, unveiling the potential for a future in which robots operate efficiently in the targeted applications, aiming to integrate seamlessly into workflows with human workers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.785
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.245
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it