Soft-Rigid Hybrid Revolute and Prismatic Joints Using Multilayered Bellow-Type Soft Pneumatic Actuators: Design, Characterization, and Its Application as Soft-Rigid Hybrid Gripper
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".