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1. Neuromuscular actuation of biohybrid motile bots

   https://doi.org/10.1073/pnas.1907051116  

   Aydin, Onur; Zhang, Xiaotian; Nuethong, Sittinon; Pagan-Diaz, Gelson J.; Bashir, Rashid; Gazzola, Mattia; Saif, M. Taher (October 2019, Proceedings of the National Academy of Sciences)

   The integration of muscle cells with soft robotics in recent years has led to the development of biohybrid machines capable of untethered locomotion. A major frontier that currently remains unexplored is neuronal actuation and control of such muscle-powered biohybrid machines. As a step toward this goal, we present here a biohybrid swimmer driven by on-board neuromuscular units. The body of the swimmer consists of a free-standing soft scaffold, skeletal muscle tissue, and optogenetic stem cell-derived neural cluster containing motor neurons. Myoblasts embedded in extracellular matrix self-organize into a muscle tissue guided by the geometry of the scaffold, and the resulting muscle tissue is cocultured in situ with a neural cluster. Motor neurons then extend neurites selectively toward the muscle and innervate it, developing functional neuromuscular units. Based on this initial construct, we computationally designed, optimized, and implemented light-sensitive flagellar swimmers actuated by these neuromuscular units. Cyclic muscle contractions, induced by neural stimulation, drive time-irreversible flagellar dynamics, thereby providing thrust for untethered forward locomotion of the swimmer. Overall, this work demonstrates an example of a biohybrid robot implementing neuromuscular actuation and illustrates a path toward the forward design and control of neuron-enabled biohybrid machines. 

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2. Optogenetic neuromuscular actuation of a miniature electronic biohybrid robot

   https://doi.org/10.1126/scirobotics.adu5830  

   Min, Hyegi; Wang, Yue; Wang, Jiaojiao; Li, Xiuyuan; Kim, Woong; Aydin, Onur; Kang, Sehong; You, Jae-Sung; Lim, Jongwon; Wolhaupter, Katy; et al (September 2025, Science Robotics)

   Neuronal control of skeletal muscle function is ubiquitous across species for locomotion and doing work. In particular, emergent behaviors of neurons in biohybrid neuromuscular systems can advance bioinspired locomotion research. Although recent studies have demonstrated that chemical or optogenetic stimulation of neurons can control muscular actuation through the neuromuscular junction (NMJ), the correlation between neuronal activities and resulting modulation in the muscle responses is less understood, hindering the engineering of high-level functional biohybrid systems. Here, we developed NMJ-based biohybrid crawling robots with optogenetic mouse motor neurons, skeletal muscles, 3D-printed hydrogel scaffolds, and integrated onboard wireless micro–light-emitting diode (μLED)–based optoelectronics. We investigated the coupling of the light stimulation and neuromuscular actuation through power spectral density (PSD) analysis. We verified the modulation of the mechanical functionality of the robot depending on the frequency of the optical stimulation to the neural tissue. We demonstrated continued muscle contraction up to 20 minutes after a 1-minute-long pulsed 2-hertz optical stimulation of the neural tissue. Furthermore, the robots were shown to maintain their mechanical functionality for more than 2 weeks. This study provides insights into reliable neuronal control with optoelectronics, supporting advancements in neuronal modulation, biohybrid intelligence, and automation. 

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3. Reinforcement learning of a multi-link swimmer at low Reynolds numbers

   https://doi.org/10.1063/5.0140662  

   Qin, Ke; Zou, Zonghao; Zhu, Lailai; Pak, On Shun (March 2023, Physics of Fluids)

   The use of machine learning techniques in the development of microscopic swimmers has drawn considerable attention in recent years. In particular, reinforcement learning has been shown useful in enabling swimmers to learn effective propulsion strategies through its interactions with the surroundings. In this work, we apply a reinforcement learning approach to identify swimming gaits of a multi-link model swimmer. The swimmer consists of multiple rigid links connected serially with hinges, which can rotate freely to change the relative angles between neighboring links. Purcell [“Life at low Reynolds number,” Am. J. Phys. 45, 3 (1977)] demonstrated how the particular case of a three-link swimmer (now known as Purcell's swimmer) can perform a prescribed sequence of hinge rotation to generate self-propulsion in the absence of inertia. Here, without relying on any prior knowledge of low-Reynolds-number locomotion, we first demonstrate the use of reinforcement learning in identifying the classical swimming gaits of Purcell's swimmer for case of three links. We next examine the new swimming gaits acquired by the learning process as the number of links increases. We also consider the scenarios when only a single hinge is allowed to rotate at a time and when simultaneous rotation of multiple hinges is allowed. We contrast the difference in the locomotory gaits learned by the swimmers in these scenarios and discuss their propulsion performance. Taken together, our results demonstrate how a simple reinforcement learning technique can be applied to identify both classical and new swimming gaits at low Reynolds numbers. 

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4. Motion Planning, Design Optimization and Fabrication of Ferromagnetic Swimmers

   Jaskaran Grover, Daniel Vedova (June 2019, Robotics science and systems)

   Small-scale robots have the potential to impact many areas of medicine and manufacturing including targeted drug delivery, telemetry and micromanipulation. This paper develops an algorithmic framework for regulating external magnetic fields to induce motion in millimeter-scale robots in a viscous liquid, to simulate the physics of swimming at the micrometer scale. Our approach for planning motions for these swimmers is based on tools from geometric mechanics that provide a novel means to design periodic changes in the physical shape of a robot that propels it in a desired direction. Using these tools, we are able to derive new motion primitives for generating locomotion in these swimmers. We use these primitives for optimizing swimming efficiency as a function of its internal magnetization and describe a principled approach to encode the best magnetization distribu- tions in the swimmers. We validate this procedure experimentally and conclude by implementing these newly computed motion primitives on several magnetic swimmer prototypes that include two-link and three-link swimmers. 

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5. Swimmers at Interfaces Enhance Interfacial Transport

   Jiayi Deng, Mehdi Molaei (February 2024, arXivorg)

   The behavior of fluid interfaces far from equilibrium plays central roles in nature and in industry. Active swimmers trapped at interfaces can alter transport at fluid boundaries with far reaching implications. Swimmers can become trapped at interfaces in diverse configurations and swim persistently in these surface adhered states. The self-propelled motion of bacteria makes them ideal model swimmers to understand such effects. We have recently characterized the swimming of interfacially-trapped Pseudomonas aeruginosa PA01 moving in pusher mode. The swimmers adsorb at the interface with pinned contact lines, which fix the angle of the cell body at the interface and constrain their motion. Thus, most interfacially-trapped bacteria swim along circular paths. Fluid interfaces form incompressible two-dimensional layers, altering leading order interfacial flows generated by the swimmers from those in bulk. In our previous work, we have visualized the interfacial flow around a pusher bacterium and described the flow field using two dipolar hydrodynamic modes; one stresslet mode whose symmetries differ from those in bulk, and another bulk mode unique to incompressible fluid interfaces. Based on this understanding, swimmers-induced tracer displacements and swimmer-swimmer pair interactions are explored using analysis and experiment. The settings in which multiple interfacial swimmers with circular motion can significantly enhance interfacial transport of tracers or promote mixing of other swimmers on the interface are identified through simulations and compared to experiment. This study identifies important factors of general interest regarding swimmers on or near fluid boundaries, and in the design of biomimetic swimmers to enhance transport at interfaces. 

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