Robust Autonomous Control of a Magnetic Millirobot in In Vitro Cardiac Flow

• URL: http://arxiv.org/abs/2604.01523v1
• Date: Thu, 02 Apr 2026 01:48:04 GMT
• Title: Robust Autonomous Control of a Magnetic Millirobot in In Vitro Cardiac Flow
• Abstract summary: This work presents a vision-guided control framework enabling precise autonomous navigation of a magnetic millirobot in an in vitro heart phantom.<n>The system integrates UNet-based localization, A* path planning, and a sliding mode controller with a disturbance observer (SMC-DOB)<n>In static fluid, the SMC-DOB achieved sub-millimeter accuracy (root-mean-square error, RMSE = 0.49 mm), outperforming PID and MPC baselines.
• Score: 4.299277902318345
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Untethered magnetic millirobots offer significant potential for minimally invasive cardiac therapies; however, achieving reliable autonomous control in pulsatile cardiac flow remains challenging. This work presents a vision-guided control framework enabling precise autonomous navigation of a magnetic millirobot in an in vitro heart phantom under physiologically relevant flow conditions. The system integrates UNet-based localization, A* path planning, and a sliding mode controller with a disturbance observer (SMC-DOB) designed for multi-coil electromagnetic actuation. Although drag forces are estimated using steady-state CFD simulations, the controller compensates for transient pulsatile disturbances during closed-loop operation. In static fluid, the SMC-DOB achieved sub-millimeter accuracy (root-mean-square error, RMSE = 0.49 mm), outperforming PID and MPC baselines. Under moderate pulsatile flow (7 cm/s peak, 20 cP), it reduced RMSE by 37% and peak error by 2.4$\times$ compared to PID. It further maintained RMSE below 2 mm (0.27 body lengths) under elevated pulsatile flow (10 cm/s peak, 20 cP) and under low-viscosity conditions (4.3 cP, 7 cm/s peak), where baseline controllers exhibited unstable or failed tracking. These results demonstrate robust closed-loop magnetic control under time-varying cardiac flow disturbances and support the feasibility of autonomous millirobot navigation for targeted drug delivery.

Related papers

• Magnetically Self-Sealed MR Haptic Actuator With PWM-Based Excitation and High-Fidelity Torque Control [10.326757545448457]
  Magnetorheological fluid (MRF)-based actuators offer a compact and rapidly controllable solution for haptic feedback.<n>Practical implementation requires reliable fluid sealing, low-hysteresis, accurate torque control, and stable long-duration operation.<n>This article presents an integrated MRF haptic system featuring a compact magnetically self-sealed rotary actuator.
  arXiv  Detail & Related papers  (2026-08-20T05:04:25Z)
• Beyond Control Points: Arcsecond Relative-Motion Estimation of Vision Measurement Platforms With Incomplete or Absent Control Fields [43.43572961146893]
  We develop a control-adaptive differential framework that estimates platform motion directly from image displacements and known 3D points.<n>We derive the rotation observability condition, a leakage bound for unmodeled translation and nonrigid point motion, and the single-point axial-prior bias law.
  arXiv  Detail & Related papers  (2026-08-14T03:41:30Z)
• Learning Control as Enabling Layer for Embodied Intelligence Research explored with Soft Robotic Swimming in diverse Flow Speeds [0.0]
  We evaluate whether augmenting PID control with a Linear Repetitive Learning Estimation Scheme (PID-LRLES) recovers tracking accuracy and repeatability under dynamic flow.<n>The LRLES generalizes classical integral action from constant to periodic, non-constant references, while using a stable transfer-function realization.<n>This approach provides an enabling layer for future robophysical studies seeking to isolate the effects of morphology, sensing, and environmental flow on aquatic locomotion.
  arXiv  Detail & Related papers  (2026-06-09T15:20:13Z)
• A tunable feedback-controlled magnetic trap for a magnet in free fall [41.89902918118875]
  We propose and demonstrate a novel master proportional-integral-differential magnetic trap (MPIDMT)<n>During the microgravity phase the system stably levitates a ferromagnetic particle against shock accelerations up to 1.5 g and resolves its motion in both a low-field (0.4 g) configuration and in pure free fall.<n>Results represent a key step toward free-fall ferromagnetic magnetometry, the long-sought direct observation of macroscopic Larmor precession, and future space-based experiments.
  arXiv  Detail & Related papers  (2026-05-31T06:56:41Z)
• Toward Safe Autonomous Robotic Endovascular Interventions using World Models [34.54099310430464]
  We investigate a world-model-based framework for autonomous endovascular navigation built on TD-MPC2.<n>We evaluate a TD-MPC2 agent trained on multiple navigation across hold out patient-specific vasculatures.<n>We benchmark its performance against the state-of-the-art Soft Actor-Critic (SAC) algorithm agent.
  arXiv  Detail & Related papers  (2026-04-22T03:32:18Z)
• A Closed-Form CLF-CBF Controller for Whole-Body Continuum Soft Robot Collision Avoidance [45.63674336069651]
  Soft continuum manipulators provide passive safety through mechanical compliance.<n>Existing approaches, such as sampling-based planning, are often computationally expensive and lack formal safety guarantees.<n>This paper presents a closed-form Control Lyapunov Function--Control Barrier Function (CLF--CBF) controller for real-time 3D obstacle avoidance.
  arXiv  Detail & Related papers  (2026-03-19T19:34:49Z)
• Residual RL--MPC for Robust Microrobotic Cell Pushing Under Time-Varying Flow [0.6053202932413693]
  Contact-rich micromanipulation in microfluidic flow is challenging because small disturbances can break pushing contact and induce large lateral drift.<n>We study planar cell pushing with a magnetic rolling microrobot that tracks a waypoint-sampled reference curve under time-varying Poiseuille flow.<n>We propose a hybrid controller that augments a nominal MPC with a learned residual policy trained by SAC.
  arXiv  Detail & Related papers  (2026-03-05T18:20:07Z)
• Fluoroscopy-Constrained Magnetic Robot Control via Zernike-Based Field Modeling and Nonlinear MPC [4.093982213892736]
  Magnetic actuation enables surgical robots to navigate complex anatomical pathways while reducing tissue trauma and improving surgical precision.<n>This paper presents a control framework that remains accurate and stable under such conditions by combining a nonlinear model predictive control framework.<n> Experimental validation is conducted with two magnetic robots in a 3D-printed fluid workspace and a spine phantom replicating drug delivery in the epidural space.
  arXiv  Detail & Related papers  (2026-02-17T04:50:18Z)
• Pitch Angle Control of a Magnetically Actuated Capsule Robot with Nonlinear FEA-based MPC and EKF Multisensory Fusion [0.3694429692322632]
  This paper presents a model-based framework for magnetic pitch control of an ingestible capsule robot actuated by a four-coil electromagnetic array.<n>Experiments on a compliant stomach-inspired surface demonstrate robust pitch reorientation from both horizontal and upright configurations.<n>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.
  arXiv  Detail & Related papers  (2026-02-11T07:59:52Z)
• Wireless Center of Pressure Feedback System for Humanoid Robot Balance Control using ESP32-C3 [0.0]
  This study proposes a wireless embedded balance system designed to maintain stability on uneven surfaces.<n>The proposed control system achieved a 100% success rate in maintaining balance during single-leg lifting tasks.
  arXiv  Detail & Related papers  (2025-12-24T15:00:23Z)
• Enhancing ECG Classification Robustness with Lightweight Unsupervised Anomaly Detection Filters [39.9470953186283]
  Continuous electrocardiogram (ECG) monitoring via wearables offers significant potential for early cardiovascular disease (CVD) detection.<n> deploying deep learning models for automated analysis in resource-constrained environments faces reliability challenges due to Out-of-Distribution data.<n>This paper explores Unsupervised Anomaly Detection (UAD) as an independent, upstream filtering mechanism to improve robustness.
  arXiv  Detail & Related papers  (2025-10-30T13:54:37Z)
• Explainable AI-Enhanced Supervisory Control for Robust Multi-Agent Robotic Systems [0.0]
  We present an explainable AI-enhanced supervisory control framework for multi-agent robotics.<n>We validated the approach in two contrasting domains, spacecraft formation flying and autonomous underwater vehicles.
  arXiv  Detail & Related papers  (2025-09-18T23:59:13Z)
• Introducing a Deep Neural Network-based Model Predictive Control Framework for Rapid Controller Implementation [41.38091115195305]
  This work presents the experimental implementation of a deep neural network (DNN) based nonlinear MPC for Homogeneous Charge Compression Ignition (HCCI) combustion control. Using the acados software package to enable the real-time implementation of the MPC on an ARM Cortex A72, the optimization calculations are completed within 1.4 ms. The IMEP trajectory following of the developed controller was excellent, with a root-mean-square error of 0.133 bar, in addition to observing process constraints.
  arXiv  Detail & Related papers  (2023-10-12T15:03:50Z)
• Real-Time Model-Free Deep Reinforcement Learning for Force Control of a Series Elastic Actuator [56.11574814802912]
  State-of-the art robotic applications utilize series elastic actuators (SEAs) with closed-loop force control to achieve complex tasks such as walking, lifting, and manipulation. Model-free PID control methods are more prone to instability due to nonlinearities in the SEA. Deep reinforcement learning has proved to be an effective model-free method for continuous control tasks.
  arXiv  Detail & Related papers  (2023-04-11T00:51:47Z)
• Neural optimal feedback control with local learning rules [67.5926699124528]
  A major problem in motor control is understanding how the brain plans and executes proper movements in the face of delayed and noisy stimuli. We introduce a novel online algorithm which combines adaptive Kalman filtering with a model free control approach.
  arXiv  Detail & Related papers  (2021-11-12T20:02:00Z)
• Direct control of high magnetic fields for cold atom experiments based on NV centers [50.591267188664666]
  In cold atomic gases the interactions between the atoms are directly controllable through external magnetic fields. Here, we overcome the limitations of such an indirect control through a direct feedback scheme. We achieve a control of better than 1 ppm after 20 minutes of integration time, ensuring high long-term stability for experiments.
  arXiv  Detail & Related papers  (2020-03-18T09:03:25Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.