Biohybrid soft microrobots are rapidly delivered to tortuous and tiny lumens deep inside the digestive system.

We report fluorescent magnetic spore–based microrobots for remote sensing of C. diff toxins in clinical stool supernatants.

Controlling a swarm of microrobots with external fields is one of the major challenges for untethered microrobots. In this work, we present a new method to generate a vortex-like paramagnetic nanoparticle swarm (VPNS) from dispersed nanoparticles with a diameter of 500 nm, using rotating magnetic fields. The VPNS exhibits a dynamic-equilibrium structure, in which the nanoparticles perform synchronized motions. The mechanisms of the pattern-generation process are analyzed, simulated, and validated by experiments. By tuning the rotating frequency of the input magnetic field, the pattern of a VPNS changes accordingly. Analytical models for estimating the areal change of the pattern are proposed, and they have good agreement with the experimental data. Moreover, reversible merging and splitting of vortex-like swarms are demonstrated and investigated. Serving as a mobile robotic end-effector, a VPNS is capable of making locomotion by tuning the pitch angle of the actuating rotating field. With a small pitch angle, e.g. 2°, the whole swarm moves as an entity, and the shape of the pattern remains intact. In addition, the trapping forces of VPNSs are verified, showing the critical input parameters of the magnetic field that affect the morphology of the swarm. Finally, we demonstrate that VPNSs pass through curved and branched channels with high positioning precision, and the access rates for targeted delivery are over 90%, which are significantly higher than those in the cases of particle swarms moving with tumbling motions.

Magnetic microrobotics has undergone approximately 20 years of development, and the robotics and control communities have contributed significant theoretical and practical results to the motion control aspects of this field. This article introduces fundamental motion principles covering individual, multiagent, and swarm control and critically reviews the state of the art along with representative results. It then describes closed-loop control (an important part of this field), including the system structure, current motion planning and control methods, and current feedback approaches. As the development of motion control in magnetic microrobotics is far from complete, especially for swarm control, its current limitations are discussed. Finally, we conclude with several challenges and future research directions.

The small size and wireless actuation of microrobots make them potential candidates for minimally invasive medicine. To advance microrobots to future clinical application, microrobotics researchers have investigated a number of key issues, in which swarm control is a primary challenge and is attracting increasing attention. As a single microrobot has limited volume and surface area, clinically relevant tasks, including in-vivo tracking, usually require simultaneous control of a large swarm of microrobots. Unlike macroscale robots, implementing on-board actuators and sensors for microrobots is challenging, which differentiates swarm microrobotics from other swarm robotics approaches. This article systematically summarizes the state of the art for this emerging field, including actuation systems with different power sources, swarm behaviors modeling and simulation, swarm control strategies, and targeted biomedical applications. Actuation principles of microrobot swarms are categorized in detail, and critical comparisons are made to provide guidance and insight for future swarm microrobotics researchers. Considering the unique features of swarm microrobotics compared to traditional swarm robotics, this article also emphasizes the modeling, simulation, and control of microrobot swarms. Furthermore, recent biomedical applications of microrobot swarms are summarized to illustrate specific application scenarios. Finally, we provide an assessment of the future directions of swarm microrobotics.