Proprioceptive Learning with Soft Polyhedral Networks

Xiaobo Liu; Xudong Han; Wei Hong; Fang Wan; Chaoyang Song

2024

10.1177/02783649241238765

International Journal of Robotics Research   影响因子和分区

0278-3649

1741-3176

Proprioception is the "sixth sense" that detects limb postures with motor neurons. It requires a natural integration between the musculoskeletal systems and sensory receptors, which is challenging among modern robots that aim for lightweight, adaptive, and sensitive designs at low costs in mechanical design and algorithmic computation. Here, we present the Soft Polyhedral Network with an embedded vision for physical interactions, capable of adaptive kinesthesia and viscoelastic proprioception by learning kinetic features. This design enables passive adaptations to omni-directional interactions, visually captured by a miniature high-speed motion-tracking system embedded inside for proprioceptive learning. The results show that the soft network can infer real-time 6D forces and torques with accuracies of 0.25/0.24/0.35 N and 0.025/0.034/0.006 Nm in dynamic interactions. We also incorporate viscoelasticity in proprioception during static adaptation by adding a creep and relaxation modifier to refine the predicted results. The proposed soft network combines simplicity in design, omni-adaptation, and proprioceptive sensing with high accuracy, making it a versatile solution for robotics at a low material cost with more than one million use cycles for tasks such as sensitive and competitive grasping and touch-based geometry reconstruction. This study offers new insights into vision-based proprioception for soft robots in adaptive grasping, soft manipulation, and human-robot interaction.

Soft robotics force and torque sensing in-finger vision proprioception

SCI ; EI

英语

第一 ; 共同第一 ; 通讯

National Natural Science Foundation of China["62206119","52335003"] ; Science, Technology, and Innovation Commission of Shenzhen Municipality["JCYJ20220818100417038","ZDSYS20220527171403009"]

Robotics

Robotics

WOS:001183970900001

SAGE PUBLICATIONS LTD

20241215771000

Human robot interaction ; Machine design ; Musculoskeletal system ; Neurons ; Sensory perception ; Tactile sensors

Biomechanics, Bionics and Biomimetics:461.3 ; Ergonomics and Human Factors Engineering:461.4 ; Biology:461.9 ; Mechanical Design:601 ; Robotics:731.5 ; Robot Applications:731.6 ; Physical Properties of Gases, Liquids and Solids:931.2

ENGINEERING

Web of Science

Southern University of Science and Technology Shenzhen, China 518055

Xiaobo Liu,Xudong Han,Wei Hong,et al. Proprioceptive Learning with Soft Polyhedral Networks[J]. International Journal of Robotics Research,2024.

Xiaobo Liu,Xudong Han,Wei Hong,Fang Wan,&Chaoyang Song.(2024).Proprioceptive Learning with Soft Polyhedral Networks.International Journal of Robotics Research.

Xiaobo Liu,et al."Proprioceptive Learning with Soft Polyhedral Networks".International Journal of Robotics Research (2024).