CORTEXA
← Browse
arxivcs.RO2026-07-24

A Monolithic Hand with Asymmetric Origami Bending and Dual-chamber Actuators

Nan Huang, Yuming Zhu, Zicong Zhang, Jianhui Liu, Xiaohuang Liu, Dihan Liu, Jiansheng Dai, Sicong Liu

The passive adaptability inherent in soft robotic hands affords them advantages in applications that require safe and compliant interaction. However, existing soft robotic hands often struggle to simultaneously achieve adequate output performance and easy manufacturing due to their complicated structures. In this paper, we introduce the asymmetric origami bending (AOB) pattern for generating bending motion and the asymmetric dual-chamber (ADC) design for obtaining multifunction capability. The AOB single (AOB-S) chamber and AOB dual-chamber (AOB-D) units are designed and constitute the finger and palm actuators of the proposed Origami-inspired SOft Robotic (OSOR) hand. The OSOR hand achieves bio-inspired fingers-palm motions and adequate output performance within a monolithic structure that significantly simplifies the manufacturing process. By defining the asymmetric ratio to characterize the geometric asymmetry of the unit, the analytical models of the AOB and ADC structures are proposed. The Finite Element Analysis tool for the design of AOB actuators is obtained by geometric analysis. The asymmetric origami design grants the integrated manufacturing of the OSOR hand through a Selective Laser Sintering printing process with a single thermoplastic polyurethane material. The model and simulations are validated by experimental results. Experiments show the finger and palm maximum bending motion range of 203° and 40°, respectively, with output forces of 6.3 N and 16 N. The OSOR hand is capable of pinching a piece of tissue, stably grasping water bottles with two fingers, palm-only grasping, and completing the power grasps in the taxonomy of manufacturing grasps. The compactness, performance, and easy manufacturing of the proposed hand benefit the development of the soft robotic hand with new possibilities.

View free PDFSource page

Related papers

arxivcs.RO2026-07-08

Soft Robotic Exogloves for Dexterous Mobility -- Towards Personalized Rehabilitation

Paul Dela Cruz, Mostafa Mo. Massoud, Jacqueline Libby

Soft robotic exogloves can provide hand rehabilitation and assistance. Fitting these gloves often relies on standardized measurements not tailored to the individual, limiting their effectiveness, especially for fine articulation necessary for dexterous manipulation. We present th…

View free PDFSource page
arxivcs.RO2026-07-16

Robust Silicone Pour Casting and Sensor Embedding Procedures for Soft Robotic Actuators

Harshit Thakker, Paul Dela Cruz, Mostafa Mo. Massoud, Jacqueline Libby

Soft robots are well-suited for applications such as rehabilitation and surgery that require adaptable and safe interaction with their environment. However, the challenges of reproducible and scalable fabrication of soft robots limit their real-world deployment. Various fabricati…

View free PDFSource page
arxivcs.RO2026-07-08

Towards Soft Robotic Exogloves for Musculoskeletal Manipulation to Reduce Pain and Spasticity

Antonia Salluce, Maeryn Erdheim, Gailen Davis, Lauren H. Sullivan, Max-William Kanz, Jacqueline Libby

Hand spasticity and resulting pain affect 12 million people worldwide, including stroke survivors, arthritis patients, and those with other muscle and nerve deficiencies. Soft robotic exogloves are being introduced to help patients enhance mobility or manage pain; however, there…

View free PDFSource page
arxivcs.RO2026-07-06

Closing the Reality Gap: Zero-Shot Sim-to-Real Deployment for Dexterous Force-Based Grasping and Manipulation

Zhe Zhao, Zhibin Li, Yilin Ou, Mengshi Qi

Human-like dexterous hands with multiple fingers offer human-level manipulation capabilities but remain difficult to train the control policies that can deploy on real hardware due to contact-rich physics and imperfect actuation. We present a sim-to-real reinforcement learning me…

View free PDFSource page
arxivcs.ROcs.AIcs.CVcs.LG2026-07-05

Mask2Real-WM: Segmentation Masks as a Sim-to-Real Bridge for Controllable Dexterous World Models

Riccardo O. Feingold, Davide Liconti, Chenyu Yang, Robert K. Katzschmann

Action-conditioned world models allow robots to predict the future consequences of candidate actions without additional physical interaction, supporting policy evaluation, planning, and data augmentation. We present Mask2Real-WM, a two-stage action-conditioned world model for dex…

View free PDFSource page