Vision-Based Automated Control of Magnetic Microrobots

Particle manipulation under X-force fields

Particle manipulation is a central technique that enhances numerous scientific and medical applications by exploiting micro- and nanoscale control within fluidic environments. In this review, we systematically explore the multifaceted domain of particle manipulation under the influence of various X-force fields, integral to lab-on-a-chip technologies. We dissect the fundamental mechanisms of hydrodynamic, gravitational, optical, magnetic, electrical, and acoustic forces and detail their individual and synergistic applications. In particular, our discourse extends to advanced multi-modal manipulation strategies that harness the combined power of these forces, revealing their enhanced efficiency and precision in complex assays and diagnostic frameworks. The integration of cutting-edge technologies such as artificial intelligence and autonomous systems further enhances the capabilities of these microfluidic platforms, leading to transformative innovations in personalized medicine and point-of-care diagnostics. This review not only highlights current technological advances, but also forecasts the trajectory of future developments, emphasizing the escalating precision and scalability essential for advancing lab-on-a-chip applications.

Optimization-based synthesis with directed cell migration

Collective behavior of biological agents from cells to herds of organisms is a fundamental feature in systems biology and in the emergence of new phenomena in the biological environment. Collective cell migration (CCM) under a physical or chemical cue is an example of this fundamental phenomenon where the individual migration of a cell is driven by the collective behavior of the neighboring cells and vice versa. The goal of this research is to discover the mathematical rules of collective cell migration with dynamic mode decomposition (DMD) with the use of experimental data and to test the predictive nature of the models with independent experimental data sets subject to Dirichlet, Neumann, and mixed boundary conditions. Both single and multi-cellular systems are investigated in this process. Additionally, the goal of this research is to create an optimal trajectory for microscopic robots in the presence of an obstacle course made of both static and dynamic obstacles. Such an optimization is made possible by synthesizing the discovered dynamics for cell migration with a numerical approach to dynamic optimization known as collocation by augmenting the discovered dynamics to the constraint equations. The optimal trajectory results presented in silico have potential design applications for the path planning of microrobots for therapeutic purposes such as cancer cell drug delivery, microsurgery, microsensing for early disease detection, and cleaning of toxic substances.

Learning a Tracking Controller for Rolling μbots

Micron-scale robots (μbots) have recently shown great promise for emerging medical applications. Accurate control of μbots, while critical to their successful deployment, is challenging. In this work, we consider the problem of tracking a reference trajectory using a μbot in the presence of disturbances and uncertainty. The disturbances primarily come from Brownian motion and other environmental phenomena, while the uncertainty originates from errors in the model parameters. We model the μbot as an uncertain unicycle that is controlled by a global magnetic field. To compensate for disturbances and uncertainties, we develop a nonlinear mismatch controller. We define the model mismatch error as the difference between our model's predicted velocity and the actual velocity of the μbot. We employ a Gaussian Process to learn the model mismatch error as a function of the applied control input. Then we use a least-squares minimization to select a control action that minimizes the difference between the actual velocity of the μbot and a reference velocity. We demonstrate the online performance of our joint learning and control algorithm in simulation, where our approach accurately learns the model mismatch and improves tracking performance. We also validate our approach in an experiment and show that certain error metrics are reduced by up to 40%.

System integration of magnetic medical microrobots: from design to control

Magnetic microrobots are ideal for medical applications owing to their deep tissue penetration, precise control, and flexible movement. After decades of development, various magnetic microrobots have been used to achieve medical functions such as targeted delivery, cell manipulation, and minimally invasive surgery. This review introduces the research status and latest progress in the design and control systems of magnetic medical microrobots from a system integration perspective and summarizes the advantages and limitations of the research to provide a reference for developers. Finally, the future development direction of magnetic medical microrobot design and control systems are discussed.

Review of Ultrasonic Particle Manipulation Techniques: Applications and Research Advances

Ultrasonic particle manipulation technique is a non-contact label-free method for manipulating micro- and nano-scale particles using ultrasound, which has obvious advantages over traditional optical, magnetic, and electrical micro-manipulation techniques; it has gained extensive attention in micro-nano manipulation in recent years. This paper introduces the basic principles and manipulation methods of ultrasonic particle manipulation techniques, provides a detailed overview of the current mainstream acoustic field generation methods, and also highlights, in particular, the applicable scenarios for different numbers and arrangements of ultrasonic transducer devices. Ultrasonic transducer arrays have been used extensively in various particle manipulation applications, and many sound field reconstruction algorithms based on ultrasonic transducer arrays have been proposed one after another. In this paper, unlike most other previous reviews on ultrasonic particle manipulation, we analyze and summarize the current reconstruction algorithms for generating sound fields based on ultrasonic transducer arrays and compare these algorithms. Finally, we explore the applications of ultrasonic particle manipulation technology in engineering and biological fields and summarize and forecast the research progress of ultrasonic particle manipulation technology. We believe that this review will provide superior guidance for ultrasonic particle manipulation methods based on the study of micro and nano operations.

A Comprehensive Review of Vision-Based Robotic Applications: Current State, Components, Approaches, Barriers, and Potential Solutions

Being an emerging technology, robotic manipulation has encountered tremendous advancements due to technological developments starting from using sensors to artificial intelligence. Over the decades, robotic manipulation has advanced in terms of the versatility and flexibility of mobile robot platforms. Thus, robots are now capable of interacting with the world around them. To interact with the real world, robots require various sensory inputs from their surroundings, and the use of vision is rapidly increasing nowadays, as vision is unquestionably a rich source of information for a robotic system. In recent years, robotic manipulators have made significant progress towards achieving human-like abilities. There is still a large gap between human and robot dexterity, especially when it comes to executing complex and long-lasting manipulations. This paper comprehensively investigates the state-of-the-art development of vision-based robotic application, which includes the current state, components, and approaches used along with the algorithms with respect to the control and application of robots. Furthermore, a comprehensive analysis of those vision-based applied algorithms, their effectiveness, and their complexity has been enlightened here. To conclude, there is a discussion over the constraints while performing the research and potential solutions to develop a robust and accurate vision-based robot manipulation.