We develop ingestible capsule robots that sense, move, and interact with the gastrointestinal environment. Our goal is to extend capsule-based examination beyond passive imaging toward controlled navigation, local mechanical sensing, and sustained monitoring of gastrointestinal function.
Our research combines magnetic actuation with miniature transducers, wireless electronics, soft test phantoms, and model-based estimation and control. Prior work on long-residence capsule systems and distributed sensors informs current efforts in magnetic navigation, IMU-based motion coherence, palpation, and compact surrogate models for real-time control.
We develop external magnetic actuation for capsule motion and controlled contact with soft surfaces. Programmable coatings enable rolling and yaw steering, while a complementary four-coil platform regulates pitch with model predictive control and IMU–camera fusion.

Programmable coating fabrication and an externally actuated capsule testbed.

A benchtop coil array tests capsule pitch regulation on a soft phantom.

MPC and IMU–camera fusion reduce oscillation during pitch reorientation.
We study how unaligned inertial sensors can recover propagating motion on deformable surfaces. Canonical maximization of coherence combines each IMU’s three gyroscope axes, and cross-correlation estimates the delay between sensors.

Embedded IMUs recover shared motion as deformation propagates through a soft phantom.

Three-axis gyroscope projections and cross-correlation estimate propagation delay.

Sliding windows track a programmed change in propagation delay.
We aim to combine magnetic capsule positioning with controlled tissue contact to measure local mechanical properties. Supporting robotic palpation experiments provide contact models and validation methods for this capsule research direction.

A KUKA-mounted voice-coil probe supports static and dynamic tissue-phantom tests.

Six internal air channels and a probing grid support robotic palpation validation.

Robotic indentation reveals shallow subsurface channels through stiffness contrast.
We develop compact magnetic torque models for capsule pitch control. Finite-element analysis supplies training data, and a small nominal model predicts torque during bounded allocation of two coil-pair currents.

A residual GP guides sampling before a compact nominal model is fitted for control.

The nominal torque model allocates two coil-pair currents within hardware limits.

Adaptive ratio preference improves tracking in the tested 20°–30° reference trials.
© MINIMAX Lab, Walker Department of Mechanical Engineering, The University of Texas at Austin. All rights reserved.