Louis William Rogowski, Yasin Cagatay Duygu, Xiao Zhang, Anuruddha Bhattacharjee, Sung Jae Park


This thesis utilizes a soft alginate microbot for targeted drug delivery. To achieve this aim, we present an adaptive backstepping controller for the reference tracking of an alginate artificial cell. An adaptive controller was implemented to precisely manipulate a magnetic artificial cell actuated by rotating magnetic fields. The rolling motion of a small-scale robot in a fluidic environment is challenging, especially when the fluid imparts an unknown response at low Reynolds number. In order to compensate for this uncertainty, an unknown tuning parameter encapsulating these effects was added to the governing equations of motion. A controller with an update law was then designed to estimate the unknown parameter and force the artificial cell to produce the desired response. The stability of the proposed controller was established by a candidate Lyapunov function. Real-time experiments were conducted to demonstrate the effectiveness of the designed controller at guiding an artificial cell to an arbitrary target position. Alginate cells were guided through a maze using the controller and were later combined with wall constraints to allow multiple alginate cells to reach the same target location. This controller can be applied to both surface motion and swimming-based small-scale robots in future applications for micro-assembly and targeted drug delivery.

To increase the drug-carrying capacity, we demonstrate a manipulation of snowman-shaped soft microrobots under a uniform rotating magnetic field for complex locomotion modes. Each microsnowman robot consists of two biocompatible alginate microspheres with embedded magnetic nanoparticles. The soft microsnowmen were fabricated using a microfluidic device by following a centrifuge-based microfluidic droplet method. Under a uniform rotating magnetic field, the microsnowmen were rolled on the substrate surface, and the velocity response for increasing magnetic field frequencies was analyzed. Then, a microsnowman was rolled to follow different paths, which demonstrated directional controllability of the microrobot. Moreover, swarms of microsnowmen and single alginate microrobots were manipulated under the rotating magnetic field, and their velocity responses were analyzed for comparison.

Moreover, the motion characteristics of soft alginate microsnowman robots were analyzed with wireless magnetic fields in complex fluidic environments. Polyacrylamide (PAA), a water-soluble polymer, was characterized to produce a challenging environment with a non-Newtonian fluid. The robots were fabricated by an extrusion-based droplet method. To increase the payload and achieve complex actuation, the shape of the soft microrobot resembles a snowman. This shape allows for the creation of complex locomotion modes. Under the rotating magnetic field, tumbling and rolling motions of the robots were achieved in non-Newtonian fluidic environment. A comparison study with respect to the traveled distance of various robots is presented to demonstrate the success of the soft sodium alginate microsnowman microrobot. Additionally, the controllability of the robots for potential use in drug delivery was shown by tracking a square pattern with swarm control.

In the last chapter, a feasibility study of our alginate robotic platform is presented. This study investigates the navigation capabilities of a mesoscale soft robot made from biocompatible alginate material in complex mazes. The primary objective is to assess the motion characteristics of these robots in a constrained environment for biomedical applications, such as targeted drug delivery or minimally invasive surgery. The soft robots were fabricated by a 3D bioprinter by using the droplet ejection method. The soft robot material, alginate, is encapsulated by using calcium chloride. In order to impart magnetic properties, paramagnetic nanoparticles were added to the encapsulated robot. This method enables precise navigation under external rotating magnetic fields. The mazes, created with silicone tubes, resemble the vascular system to create a realistic and constrained environment.

Degree Date

Spring 5-11-2024

Document Type


Degree Name



Mechanical Engineering


MinJun Kim

Number of Pages




Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License