Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.10610 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866918332162113536 |
|---|---|
| author | Wang, Chongxun Shen, Zikang Rathore, Apoorav Udombeh, Akanimoh Teng, Harrison Xia, Fangzhou |
| author_facet | Wang, Chongxun Shen, Zikang Rathore, Apoorav Udombeh, Akanimoh Teng, Harrison Xia, Fangzhou |
| contents | Magnetically actuated capsule robots promise minimally invasive diagnosis and therapy in the gastrointestinal (GI) tract, but existing systems largely neglect control of capsule pitch, a degree of freedom critical for contact-rich interaction with inclined gastric walls. This paper presents a nonlinear, model-based framework for magnetic pitch control of an ingestible capsule robot actuated by a four-coil electromagnetic array. Angle-dependent magnetic forces and torques acting on embedded permanent magnets are characterized using three-dimensional finite-element simulations and embedded as lookup tables in a control-oriented rigid-body pitching model with rolling contact and actuator dynamics. A constrained model predictive controller (MPC) is designed to regulate pitch while respecting hardware-imposed current and slew-rate limits. Experiments on a compliant stomach-inspired surface demonstrate robust pitch reorientation from both horizontal and upright configurations, achieving about three to five times faster settling and reduced oscillatory motion than on-off control. Furthermore, an extended Kalman filter (EKF) fusing inertial sensing with intermittent visual measurements enables stable closed-loop control when the camera update rate is reduced from 30 Hz to 1 Hz, emulating clinically realistic imaging constraints. These results establish finite-element-informed MPC with sensor fusion as a scalable strategy for pitch regulation, controlled docking, and future multi-degree-of-freedom capsule locomotion. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_10610 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Pitch Angle Control of a Magnetically Actuated Capsule Robot with Nonlinear FEA-based MPC and EKF Multisensory Fusion Wang, Chongxun Shen, Zikang Rathore, Apoorav Udombeh, Akanimoh Teng, Harrison Xia, Fangzhou Robotics Magnetically actuated capsule robots promise minimally invasive diagnosis and therapy in the gastrointestinal (GI) tract, but existing systems largely neglect control of capsule pitch, a degree of freedom critical for contact-rich interaction with inclined gastric walls. This paper presents a nonlinear, model-based framework for magnetic pitch control of an ingestible capsule robot actuated by a four-coil electromagnetic array. Angle-dependent magnetic forces and torques acting on embedded permanent magnets are characterized using three-dimensional finite-element simulations and embedded as lookup tables in a control-oriented rigid-body pitching model with rolling contact and actuator dynamics. A constrained model predictive controller (MPC) is designed to regulate pitch while respecting hardware-imposed current and slew-rate limits. Experiments on a compliant stomach-inspired surface demonstrate robust pitch reorientation from both horizontal and upright configurations, achieving about three to five times faster settling and reduced oscillatory motion than on-off control. Furthermore, an extended Kalman filter (EKF) fusing inertial sensing with intermittent visual measurements enables stable closed-loop control when the camera update rate is reduced from 30 Hz to 1 Hz, emulating clinically realistic imaging constraints. These results establish finite-element-informed MPC with sensor fusion as a scalable strategy for pitch regulation, controlled docking, and future multi-degree-of-freedom capsule locomotion. |
| title | Pitch Angle Control of a Magnetically Actuated Capsule Robot with Nonlinear FEA-based MPC and EKF Multisensory Fusion |
| topic | Robotics |
| url | https://arxiv.org/abs/2602.10610 |