0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessA homogeneous pneumatic soft robot may generate complex output motions using a simple input pressure, resulting from its morphological shape that locally deforms the soft material to different degrees by simultaneously tailoring the structural characteristics and orienting the input pressure. To date, design of the morphological shape (inverse problem) has not been fully addressed. This article outlines a geometry–mechanics–optimization integrated approach to automatically shaping a pneumatic soft actuator or robot that achieves the desired deformation behavior. Instead of constraining the robot's geometry within any predefined regular shape, we employ B-splines to allow generation of freeform boundary surfaces, and use nonlinear mechanical modelling and shape derivative based optimization to navigate the high-dimensional design space. Our design framework can readily regulate the surface quality during the morphological evolution, by imposing the geometric constraints in terms of the principal curvatures and the minimal distance between surfaces as penalty functions. The effect of external forces including the gravity and the interaction force at the end-effector is also taken into account to generalize the method for design problems in which the load capability is also pursued. To improve the computational efficiency, suboptimization problems are constructed within a trust region in which the displacement-dependent objective function is approximated by its first-order Taylor polynomial based on the gradient information to avoid frequently performing time-consuming nonlinear finite element analysis. The suboptimization problems are then solved by the quasi-Newton method combined with the backtracking line search strategy. We showcase various applications to validate our design approach, including actuators for basic extension, bending, and twisting motions, and continuous robot arms that can perform desired in-plane and out-of-plane configurations. We also show that our method can address design of multiple chambers for achieving multiple target deformation behaviors, by co-optimizing the morphological shape and air pressures, which is validated by two examples.
Feifei Chen, Zenan Song, Shitong Chen, Guoying Gu, Xiangyang Zhu (2023). Morphological Design for Pneumatic Soft Actuators and Robots With Desired Deformation Behavior. IEEE Transactions on Robotics, 39(6), pp. 4408-4428, DOI: 10.1109/tro.2023.3323825.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2023
Authors
5
Datasets
0
Total Files
0
Language
English
Journal
IEEE Transactions on Robotics
DOI
10.1109/tro.2023.3323825
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access