Microrobot Research Articles

Towards Safe Control of Continuum Manipulator Using Shielded Multiagent Reinforcement Learning

Continuum robotic manipulators are increasingly adopted in minimal invasive surgery. However, their nonlinear behavior is challenging to model accurately, especially when subject to external interaction, potentially leading to poor control performance. In this letter, we investigate the feasibility of adopting a model-free multiagent reinforcement learning (RL), namely multiagent deep Q network (MADQN), to control a 2-degree of freedom (DoF) cable-driven continuum surgical manipulator. The control of the robot is formulated as a one DoF, one agent problem in the MADQN framework to improve the learning efficiency. Combined with a shielding scheme that enables dynamic variation of the action set boundary, MADQN leads to efficient and importantly safer control of the robot. Shielded MADQN enabled the robot to perform point and trajectory tracking with submillimeter root mean square errors under external loads, soft obstacles, and rigid collision, which are common interaction scenarios encountered by surgical manipulators. The controller was further proven to be effective in a miniature continuum robot with high structural nonlinearitiy, achieving trajectory tracking with submillimeter accuracy under external payload.

Gait and locomotion analysis of a soft-hybrid multi-legged modular miniature robot

The locomotion performance of the current legged miniature robots remains inferior compared to even the most simple insects. The inferiority has led researchers to utilize biological principles and control in their designs, often resulting in improved performance and robot capabilities. Additionally, optimizing the locomotion patterns compatible with the robot’s limitations (such as the gaits achievable by the robot) improves the performance significantly and results in a robot operating with its maximum capabilities. This paper studies the locomotion characteristics of running/walking n-legged modular miniature robots with soft or rigid module connections. The locomotion study is done using the presented dynamic model, and the results are verified using a legged modular miniature robot with soft and rigid backbones (SMoLBot). The optimum foot contact sequences for an n-legged robot with different compliance values between the modules are derived using the locomotion analyses and the dynamic and kinematic formulations. Our investigations determine unique optimum foot contact sequences for multi-legged robots with different body compliances and module numbers. Locomotion analyses of a multi-legged robot with different backbones operating with optimum gaits show two main motion characteristics; the rigid robots minimize the number of leg-ground contacts to increase velocity, whereas soft-backbone robots use a lift–jump–fall motion sequence to maximize the translational speeds. These two behaviors are similar between different soft-backbone and rigid-backbone robots; however, the optimal foot contact sequences are different and unpredictable.

A magnetically controlled soft miniature robotic fish with a flexible skeleton inspired by zebrafish

The untethered miniature swimming robot actuation and control is difficult as the robot size becomes smaller, due to limitations of feasible miniaturized on-board components. Nature provides much inspiration for developing miniature robot. Here, a new artificial untethered miniature robotic fish with a flexible magnetic skeleton and soft body that achieve controlled locomotion under the water through an external magnetic field is presented. The soft body of the shuttle-shaped structure microrobot was manufactured from pure Ecoflex, while the skeleton for magnetic actuation was manufactured from Ecoflex and NdFeB composites in a certain ratio and was endowed with a special magnetization profile. Microrobots that experience external magnetic fields are able to swim underwater and have environmental adaptations that include the flexibility to traverse aquatic plants area and crushed stone terrain. The robot also exhibits friendly interactivity and camouflage ability to get close to the zebrafish without scaring them. Moreover, the soft miniature robotic fish could be used to study the impacts of the morphology and kinematics changing in zebrafish populations.

Assessment of Miniature Piezoelectric Travelling-Wave Beam and Plate Robots

Different up-to-date utilizations have found several benefits in condensing the size of autonomous robots. Miniature traveling wave piezoelectric robots have proven to be appropriate for many of these applications. The principles of locomotion embraced in these robots are mainly inspired by natural biological locomotion and could be categorized by their movement through a specific medium. In this article, after having highlighted the amplifying effect of piezoelectric actuators generating the locomotion necessary for robotic requests, we will review the different types of such locomotion. Next, we will discuss the traveling wave piezoelectric resonant robots. Succeeding, we will look at the operation and usages of piezoelectric beam and plate robots. Finally, we will discuss the modeling aspects implicated in these robots and more generally, the modeling of piezoelectric patches stuck on thin structures. Keywords: piezoelectric, miniature, travelling-wave, locomotion, beam and plate robots

A Data-Driven Soft Sensor for Swarm Motion Speed Prediction Using Ensemble Learning Methods

Machine Learning (ML) for swarm motion prediction is a relatively unexplored area that could help sustain and monitor daily swarm robotics collective tasks. This paper focuses on a specific application of swarm robotics which is pattern formation, to demonstrate the ability of Ensemble Learning (EL) approaches to predict the motion speed of swarm robots. Specifically, the boosted trees (BST) and bagged trees (BT) algorithms are introduced to predict the motion speed of a swarm of miniature two-wheels differential driver mobile robots performing a circle-formation via the viscoelastic control model. This choice's motivation is due to EL-based models' ability to improve the performance of ML models by combining multiple learners versus single regressors. Both BST and BT algorithms' performances are compared to ten commonly known prediction models based on Support Vector Regressors (SVRs) and Gaussian Process Regressors (GPRs) with different kernel functions. Using simulated measurements recorded every 0.1 second from the robots' sensors, we demonstrate the effectiveness of the developed methods over conventional ML models (SVR and GPR) in a free/non-free obstacles environment. Results showed that the BST and BT regression models reached the highest prediction performance with fully and partially connected swarms and even when involving different swarm sizes.

Visible Light-Driven Jellyfish-like Miniature Swimming Soft Robot.

Soft actuators that exhibit large deformation and can move at a fast speed in response to external stimuli have been in high demand for biomimetic applications. In this paper, we propose a convenient approach to fabricate a reversible and thermal-responsive composite hydrogel. Under the irradiation of visible light, the striped hydrogel can bend at a speed of up to 65.72°/s with carbon nanotubes loaded at a concentration of 3 mg/mL. A jellyfish-like miniature soft robot is made using this hydrogel. When driven by visible light, the robot can move at a maximum speed of 3.37 mm/s. Besides swimming, other motion modes, including walking and jumping, are also achieved by the robot. In addition, the robot can perform directional transportation of tiny objects. As a new actuation approach for the research of jellyfish-like miniature soft robots, this work is of great significance to the development of flexible bionic robots. Moreover, this work also offers some important insights into the research of biomimetic robots driven by visible light.

A Digitized Representation of the Modified Prandtl-Ishlinskii Hysteresis Model for Modeling and Compensating Piezoelectric Actuator Hysteresis.

Piezoelectric actuators are widely used in micromanipulation and miniature robots due to their rapid response and high repeatability. The piezoelectric actuators often have undesired hysteresis. The Prandtl–Ishlinskii (PI) hysteresis model is one of the most popular models for modeling and compensating the hysteresis behaviour. This paper presents an alternative digitized representation of the modified Prandtl–Ishlinskii with the dead-zone operators (MPI) hysteresis model to describe the asymmetric hysteresis behavior of piezoelectric actuators. Using a binary number with n digits to represent the classical Prandtl–Ishlinskii hysteresis model with n elementary operators, the inverse model can be easily constructed. A similar representation of the dead-zone operators is also described. With the proposed digitized representation, the model is more intuitive and the inversion calculation is avoided. An experiment with a piezoelectric stacked linear actuator is conducted to validate the proposed digitized MPI hysteresis model and it is shown that it has almost the same performance as compared to the classical representation.

Miniature parallel robot with submillimeter positioning accuracy for minimally invasive laser osteotomy

AbstractTo overcome the physical limitations of mechanical bone cutting in minimally invasive surgery, we are developing a miniature parallel robot that enables positioning of a pulsed laser with an accuracy below 0.25 mm and minimizes the required manipulation space above the target tissue. This paper presents the design, control, device characteristics, functional testing, and performance evaluation of the robot. The performance of the robot was evaluated within the scope of a path-following experiment. The required accuracy for continuous cuts was achieved and reached 0.176 mm on the test bench.

A framework for dynamic modeling of legged modular miniature robots with soft backbones

In this work, the dynamics of ”n” legged modular miniature robots with a soft body is modeled. The dynamic formulation is obtained using Newton–Euler formulation that depends on the contact parameters and the feet closed-chain kinematic analysis. The dynamic model determines the locomotion parameters of each module as an individual system as well as the dynamics of the whole robot in a 3D space; i.e., the robot is modeled as one system, and modules are considered to be sets of flexible links connected within this system. Kinematic constraints among these modules are obtained by considering the type of backbone integrated into the modular robot. Various types of backbones are used that are classified into three groups: rigid, only torsional, and soft. The model is verified using SMoLBot, an origami-inspired miniature robot made of multiple modules and soft/rigid backbones. Additional to the dynamic model, the effect of different sets of design parameters on the locomotion of the legged soft-bodied modular miniature robots is studied. Analyses comparing the velocity of SMoLBot with a different number of modules and various types of backbones are presented using the proposed dynamic model. Our results show the existence of an optimum backbone torsional stiffness for legged miniature modular robots and an optimum number of legs for a given backbone stiffness that maximizes the robot’s velocity. In this research, presented results and locomotion study show that the robot’s design should be iteratively improved based on specific optimum goals for exclusively defined task to satisfy the operational needs.

Carbon fiber–aluminum sandwich for micro-aerial vehicles and miniature robots

Carbon fiber–aluminum sandwich for micro-aerial vehicles and miniature robots

Design, modeling and control of a miniature bio-inspired amphibious spherical robot

It is a huge challenge for an amphibious robot with a high locomotory performance to locomote in amphibious environments, including crawling on rough terrains, maneuvering underwater, and launching and landing motion between land and water. To deal with such a challenge, a miniature bio-inspired Amphibious Spherical Robot (ASRobot) with a Legged, Multi-vectored Water-jet Composite Driving Mechanism (LMWCDM) has been designed. In this paper, locomotory performance of the robot in amphibious field environments is studied. First, a simplified kinematic model was built to study crawling gaits, and with an online adjustment mechanism, the gaits were adjusted, enabling the robot to climb up slopes more stably. Then, using a dynamic underwater model, a real-time dynamic thrust vectoring allocation strategy is proposed to generate the water-jet thrust and joint angles using desired forces and torques computed by four parallel PID algorithms. Finally, a set of experiments were carried out to evaluate the performance of on land locomotion and underwater locomotion. Further, outdoor locomotion experiments including crawling on various terrains, launching and landing motion, were conducted in field environments. The results demonstrate that the robot prototype possesses the high locomotory performance which endows its wide application of disaster rescue, reconnaissance and resource exploration in amphibious environments.

Self-adaptive and efficient propulsion of Ray sperms at different viscosities enabled by heterogeneous dual helixes

We disclose a peculiar rotational propulsion mechanism of Ray sperms enabled by its unusual heterogeneous dual helixes with a rigid spiral head and a soft tail, named Heterogeneous Dual Helixes (HDH) model for short. Different from the conventional beating propulsion of sperm, the propulsion of Ray sperms is from both the rotational motion of the soft helical tail and the rigid spiral head. Such heterogeneous dual helical propulsion style provides the Ray sperm with high adaptability in viscous solutions along with advantages in linearity, straightness, and bidirectional motion. This HDH model is further corroborated by a miniature swimming robot actuated via a rigid spiral head and a soft tail, which demonstrates similar superiorities over conventional ones in terms of adaptability and efficiency under the same power input. Such findings expand our knowledge on microorganisms' motion, motivate further studies on natural fertilization, and inspire engineering designs.

Magnetic Robots: Small‐Scale Magnetic Actuators with Optimal Six Degrees‐of‐Freedom (Adv. Mater. 23/2021)

Magnetic miniature robots have great potential to create a paradigm shift for robotics, materials science, and biomedicine because they can non-invasively access highly confined and enclosed spaces to perform a vast range of small-scale manipulation tasks. In article number 2100170, Guo Zhan Lum and co-workers introduce optimal magnetic miniature robots that can display unprecedented dexterity, manipulation capabilities, and functionalities.

Wireless MRI-Powered Reversible Orientation-Locking Capsule Robot.

Magnetic resonance imaging (MRI) scanners do not provide only high‐resolution medical imaging but also magnetic robot actuation and tracking. However, the rotational motion capabilities of MRI‐powered wireless magnetic capsule‐type robots have been limited due to the very high axial magnetic field inside the MRI scanner. Medical functionalities of such robots also remain a challenge due to the miniature robot designs. Therefore, a wireless capsule‐type reversible orientation‐locking robot (REVOLBOT) is proposed that has decoupled translational motion and planar orientation change capability by locking and unlocking the rotation of a spherical ferrous bead inside the robot on demand. Such an on‐demand locking/unlocking mechanism is achieved by a phase‐changing wax material in which the ferrous bead is embedded inside. Controlled and on‐demand hyperthermia and drug delivery using wireless power transfer‐based Joule heating induced by external alternating magnetic fields are the additional features of this robot. The experimental feasibility of the REVOLBOT prototype with steerable navigation, medical function, and MRI tracking capabilities with an 1.33 Hz scan rate is demonstrated inside a preclinical 7T small‐animal MRI scanner. The proposed robot has the potential for future clinical use in teleoperated minimally invasive treatment procedures with hyperthermia and drug delivery capabilities while being wirelessly powered and monitored inside MRI scanners.

Small-Scale Magnetic Actuators with Optimal Six Degrees-of-Freedom.

Magnetic miniature robots (MMRs) are small-scale, untethered actuators which can be controlled by magnetic fields. As these actuators can non-invasively access highly confined and enclosed spaces; they have great potential to revolutionize numerous applications in robotics, materials science, and biomedicine. While the creation of MMRs with six-degrees-of-freedom (six-DOF) represents a major advancement for this class of actuators, these robots are not widely adopted due to two critical limitations: i) under precise orientation control, these MMRs have slow sixth-DOF angular velocities (4degree s-1 ) and it is difficult to apply desired magnetic forces on them; ii) such MMRs cannot perform soft-bodied functionalities. Here a fabrication method that can magnetize optimal MMRs to produce 51-297-fold larger sixth-DOF torque than existing small-scale, magnetic actuators is introduced. A universal actuation method that is applicable for rigid and soft MMRs with six-DOF is also proposed. Under precise orientation control, the optimal MMRs can execute full six-DOF motions reliably and achieve sixth-DOF angular velocities of 173degree s-1 . The soft MMRs can display unprecedented functionalities; the six-DOF jellyfish-like robot can swim across barriers impassable by existing similar devices and the six-DOF gripper is 20-folds quicker than its five-DOF predecessor in completing a complicated, small-scale assembly.

Moving Mechanism of a High-speed Insect-scale Microrobot via Electromagnetically Induced Vibration

Moving Mechanism of a High-speed Insect-scale Microrobot via Electromagnetically Induced Vibration

Dual high-stroke and high-work capacity artificial muscles inspired by DNA supercoiling.

Powering miniature robots using actuating materials that mimic skeletal muscle is attractive because conventional mechanical drive systems cannot be readily downsized. However, muscle is not the only mechanically active system in nature, and the thousandfold contraction of eukaryotic DNA into the cell nucleus suggests an alternative mechanism for high-stroke artificial muscles. Our analysis reveals that the compaction of DNA generates a mass-normalized mechanical work output exceeding that of skeletal muscle, and this result inspired the development of composite double-helix fibers that reversibly convert twist to DNA-like plectonemic or solenoidal supercoils by simple swelling and deswelling. Our modeling-optimized twisted fibers give contraction strokes as high as 90% with a maximum gravimetric work 36 times higher than skeletal muscle. We found that our supercoiling coiled fibers simultaneously provide high stroke and high work capacity, which is rare in other artificial muscles.

Visual inspection for transformer insulation defects by a patrol robot fish based on deep learning

In order to effectively detect the internal insulation defects of large transformers, a miniature patrol robot fish is designed and used to observe the pressboard inside the transformer, which can visually inspect the insulation condition of the pressboard. In the process of visual inspection by a patrol robot fish, insulation defects observed in the transformer (such as discharge carbon marks, pressboard cracks, etc.) are small size, indistinctive colour contrast and different shapes. The key purpose of the patrol robot fish is to identify the defect targets and defect types intelligently and quickly from the images taken by the camera on the fish. Considering that there are abundant insulation defects in transformers and a lack of samples for learning, a vision detection method based on deep learning network is proposed in this study. The proposed method integrates the variable autoencoder into the traditional Faster-RCNN target detection network and constructs an improved Faster-RCNN that enhances feature extraction. This method expands the small-scale training sample set and improves the generalisation performance of the model. In order to verify the effectiveness of the proposed method, the improved network is trained and tested, and the test results show that the improved network training model can accurately identify and mark the carbon marks on the pressboard surface.

SDP-Based Robust Formation-Containment Coordination of Swarm Robotic Systems with Input Saturation

There are many potential applications of swarm robotic systems in real-world scenarios. In this paper, formation-containment controller design for single-integrator and double-integrator swarm robotic systems with input saturation is investigated. The swarm system contains two types of robots—leaders and followers. A novel control protocol and an implementation algorithm are proposed that enable the leaders to achieve the desired formation via semidefinite programming (SDP) techniques. The followers then converge into the convex hull formed by the leaders simultaneously. In contrast to conventional consensus-based formation control methods, the relative formation reference signal is not required in the real-time data transmission, which provides greater feasibility for implementation on hardware platforms. The effectiveness of the proposed formation-containment control algorithm is demonstrated with both numerical simulations and experiments using real robots that utilize the miniature mobile robot, Mona.

Design and Demonstration of a Flying-Squirrel-Inspired Jumping Robot with Two Modes

The jumping–gliding robot is a kind of locomotion platform with the capabilities to jump on the ground and glide through the air. The jumping of this robot has to juggle the requirements of initial velocity and posture for entry to gliding and progressing on the ground. Inspired by flying squirrels, we proposed the concept of flexible wing-limb blending platform and designed a robot with two jumping modes. The robot can takeoff with different speeds and stances, and adjust aerial posture using the swing of forelimbs. To the best of our knowledge, this is the first miniature and bio-inspired jumping robot that can autonomically change the speeds and stances when takeoff. Experimental results show that the robot can takeoff at about 3 m/s and pitch angle of 0° in the mode of jumping for gliding and adjust the pitch angle at the top to 0°~10° by actuating the forelimbs swing according to the requirement of gliding. In the mode of jumping for progress, the robot can takeoff at about 2 m/s with a pitch angle of 20° and then intermittently jump with a distance of 0.37 m of once jump and an average progress speed of 0.2 m/s. The robot presented in this paper lays the foundation for the development of flexible wing-limb blending platform, which is capable of jumping and gliding.