Physically intelligent capsule robots with embodied memory and logic in the gastrointestinal tract

H Huyue Chen (Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong) X Xurui Liu (Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong) J Jiahai Ma (Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong) Y Yishen Zhao (Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong) C Chaoyu Yang (Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong) K Kai-Fung Chan (Chow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong) P Philip Wai Yan Chiu (Chow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong) L Lei Shao (Global College, Shanghai Jiao Tong University) W Wenming Zhang (State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University) L Li Zhang Q Qiguang He (Department Mechanical and Automation Engineering) M Metin Sitti

Abstract

Miniaturized medical robots offer a promising solution for minimally invasive measurements and interventions in the gastrointestinal (GI) tract. Clinical assessment of GI disorders is commonly guided by threshold-based physiological indicators, including pressure, temperature, and pH, which motivate event-triggered strategies for personalized medicine. However, identifying homeostatic dysregulation and enabling in-situ therapy remains challenging, because ingestible robotic systems must tightly integrate sensing, decision-making, and actuation under severe constraints of size, power, and biosafety. Inspired by the autonomy of microorganisms that operate without neural processing, this work introduces physically intelligent capsule robots (PI Capbots) that enable homeostatic monitoring and targeted delivery within the GI tract, without relying on centralized electronic control. Through embodied stimuli-responsive memory and logic, PI Capbots effectively distill rich, detailed, and redundant physiological information into a small set of decoupled and event-triggered outputs suitable for operations in in vivo environments. In each PI Capbot, multistable metamaterials encode intraluminal pressure as mechanical memory, programmable hydrogels implement orthogonal sensing and logic operations, and helical fibers enable multimodal locomotion. Ex vivo and in vivo studies in large animal models demonstrate the efficacy, robustness, and reproducibility of PI Capbots, highlighting its potential for their translational medical applications.

Article Details

Volume / Issue Vol. 123, Issue 28
Published July 14, 2026
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (12)

H

Huyue Chen

Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong

X

Xurui Liu

Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong

J

Jiahai Ma

Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong

Y

Yishen Zhao

Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong

C

Chaoyu Yang

Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong

K

Kai-Fung Chan

Chow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong

P

Philip Wai Yan Chiu

Chow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong

L

Lei Shao

Global College, Shanghai Jiao Tong University

W

Wenming Zhang

State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University

L

Li Zhang

Q

Qiguang He

Department Mechanical and Automation Engineering

M

Metin Sitti