Navigation control of microrobots in vivo has great potential in precision medicine and has attracted considerable attention in recent years. The control performance of the existing methods is considerably affected by hysteresis nonlinearity. This article presents a robust control method that can overcome hysteresis influence in navigating a microrobot actuated by an electromagnetic coil system. A motion planner that combines the breadth-first search (BFS) method and genetic algorithm (GA) is used to plan a reliable and flexible trajectory for the microrobot navigation. To compensate for hysteresis nonlinearity existing in the system, the Prandtl–Ishlinskii (PI) model is introduced. A robust controller that integrates adaptive sliding mode control (ASMC) and nonlinear disturbance observer is designed to guarantee the stability and accuracy of the microrobot in motion. Experiments have been performed to demonstrate the effectiveness of the proposed approach. The success of this research will advance the microrobot navigation for in vivo applications. Note to Practitioners—The motivation of this article is to eliminate the effect of hysteresis caused by the electromagnetic system on microrobot motion. Existing research on hysteresis compensation mostly uses inverse model or online model identification, which is not suitable for real-time control of the microrobot. In addition, the disturbance and uncertainty caused by the microfluidic environment at different flow rates will also affect the control performance of the microrobot. To solve the above problems, an adaptive robust control method is developed in this article. Experimental results have shown that the proposed method can successfully control the microrobot in the in vitro and in vivo environment.

Automatic 3D navigation control of microrobot in large microenvironment is one of the primary challenges hindering its applications. In this article, we present a systematic approach to use an electromagnetic manipulation system to deal with this challenge. Two movable orthogonal microscopic cameras scan the microenvironment on the top view and side view to build a stereo occupancy map automatically. The initial position of microrobot can be located on the basis of the similarity curves generated by the scanning sequences. In accordance with the distribution characteristic of electromagnetic fields in workspace, an enhanced rapidly exploring random tree algorithm is proposed to avoid obstacles in the complex environment. To ensure continuous visual servo in wide range, a field-of-view tracking method is developed using a specific image definition evaluation algorithm. A prescribed performance controller with disturbance observer is designed, which guarantees that the microrobot can remain in the view of microscopic cameras, and the transient and steady-state performance of the system can satisfy the expected requirements. A set of experiments are performed to verify the effectiveness of the proposed automatic 3D navigation strategy. Experimental results show that the microrobot can navigate automatically in a$\boldsymbol{12}\,\times 10\,\times \text{10-mm}$microenvironment containing obstacles, and achieve reliable field-of-view tracking and path following at high speed.

Microrobots show great targeted-delivery potential in precision medicine. This article presents the use of a model-free approach to the navigation control of a microrobot in the cardiovascular environment. With the proposed approach, the microrobot can adapt to the non-Newton behavior of blood and environmental disturbances when it moves in blood vessels without knowledge of blood-velocity distribution. The referred trajectory of the navigated microrobot is generated by using a breadth-first search and genetic algorithm, aiming to minimize the energy consumption. The proposed navigation controller combines sliding mode control, backstepping control, and disturbance compensation. A high-gain extended state observer is designed to estimate and reject the uncertainties of model parameters and environmental disturbances. Simulations are performed to demonstrate the effectiveness of the proposed approach in a small artery compared with other control methods.