Automated navigation control of microrobots in complex environments is essential for applications such as targeted drug delivery and micromanipulation. Recently, machine learning (ML) has shown great potential for automated microrobot control but still lacks accuracy and smoothness. In this work, we propose a novel Learning-from-Demonstration (LfD)-based control and navigation framework to achieve precise and smooth motion control of microrobots. This work represents an early attempt to directly utilize expert-provided data for designing a learning-based microrobot controller. The framework begins by collecting a small dataset of expert demonstrations (several thousand episodes) , from which the controller learns compensatory behaviors and task-specific adaptability, eliminating the need for extensive exploration or parameter retuning. Based on this data, a time-series neural network is then developed to process the microrobot’s historical states and control actions, allowing the system to capture sequential dependencies and transitions for smooth and accurate path tracking. For demonstration, we take the magnetic microswarm as an illustrative example. Systematic simulations and comparative experiments validate the proposed framework, demonstrating its superior performance in tracking accuracy and smoothness, validating the efficacy of ML for low-level microrobot control.

Motion control of magnetic microswarms has attracted extensive attention due to its significance in microrobots-based biomedical applications such as targeted drug delivery. However, such reconfigurable microswarms are subject to complex interactions between individuals and environments which make accurate modeling challenging. These complexities of microswarms poses challenges for precise motion control, as traditional controllers often rely on precise mathematical models and manual parameter tuning that limits their scalability and efficiency. Learning-based methods, such as Deep Reinforcement Learning (DRL), offer an alternative but require large datasets (usually on the order of millions) and extensive exploration which may cause the microswarms instability in physical environments due to unreasonable actions during early training therefore results in the sim-to-real gap. Moreover, traditional DRL focuses on instantaneous state-action mappings, neglecting the sequential dependencies critical for accurate motion control, leading to low tracking accuracy in complex scenarios. To address these challenges, we propose a Learning from Demonstration (LfD)-based motion control framework, which inherently encode compensatory behaviors and task-specific adaptability into neural networks, enabling adaptive performance even under unmodeled disturbances. Furthermore, the neural networks consider a time series of microswarm states to determine the future control actions, enabling the system to learn sequential dependencies and transitions between states so as to ensure smooth and accurate motion control. Simulations and comparative experiments validate our framework’s effectiveness and demonstrate superior control accuracy and adaptability to microswarm’s shape changes.

Motion planning of cable-driven parallel robots (CDPRs) suffers from difficulties imposed by the flexibility and unilateral property of cables. Existing methods either rely on specific motion primitives or employ complex numerical search or optimization processes, which cannot be applied to real-time applications with arbitrary path constraints. Aiming to narrow this research gap, this paper proposes a look-ahead online scaling approach to generate feasible trajectories of CDPRs subject to cable velocity, acceleration, jerk and tension constraints. Firstly, based on a desired path, the constraint equations are converted into the equivalent bounds on the path states by a look-ahead bounds estimation module. Then the timing law is online scaled by three cascaded controllers to fulfill the estimated bounds. Finally, the scaled timing law and the desired path are combined to form the final trajectory. Comparative studies on a laboratory-developed CDPR prototype demonstrate that the proposed approach outperforms state-of-the-art methods in terms of solution quality and computation time. Note to Practitioners–This paper was motivated by the problem of generating feasible trajectories of cable-driven parallel robots (CDPRs) subject to cable velocity, acceleration, jerk and tension constraints. Existing approaches either rely on specific motion primitives or employ complex numerical search or optimization processes, which cannot be applied to real-time applications with arbitrary path constraints. This paper proposes a look-ahead online scaling approach to generate feasible trajectories of CDPRs subject to these constraints. The approach uses a look-ahead bounds estimation module to determine the constraint bounds on the path states and preserve the stability of the approach. And a cascaded trajectory scaling algorithm is designed to steer the constrained path states to track a reference signal. A theoretical proof of the convergence of the scaling algorithm is provided. Through comparative studies, we show that the approach outperforms state-of-the-art methods in terms of solution quality and computation time. Experiments on a real robot prototype indicate that our method effectively improves motion accuracy and alleviates robot vibrations by considering the jerk constraints.

The dual-arm space robot usually forms a closed-chain constraint system with a target through collaborative operations when performing tasks. Most previous related research has focused on the performance of open-chain robots themselves. Studying the manipulation performance of a closed-chain robot system is of great significance. This article proposes a reconfigurable space robot (RSR) system for on-orbit servicing. A graph theory based framework for the automatic generation of reconfigurable robot models is proposed to address the characteristics of variable topology structures. Meanwhile, a new index – the closed-chain inertia matching index is proposed to evaluate its configuration effectively. Compared with traditional dynamic manipulability ellipsoid (DME) and manipulating force ellipsoid (MFE), the effectiveness of the proposed closed-chain inertia matching ellipsoid (IME) is verified. Compared with the DME and MFE, the IME effectively considers the influence of load and can effectively express the dynamic torque force/torque transmission efficiency from the joint actuator to the load in a closed-chain system. The IME can not only be used to determine the optimal joint configuration under a specific closed-chain configuration, but also to determine the optimal nonisomorphic configuration of a reconfigurable robot. Finally, the results of configuration optimization of the closed-chain dual-arm reconfigurable space robot are given.Note to Practitioners—This paper aims to study the determination of the optimal configuration for the RSR during task execution. Due to its various configurations, the RSR has a complex modeling process. This article proposes a modeling framework for automatically generating RSR models that can effectively achieve automatic modeling of various configurations. In addition, most of the previous related research focused on the performance of open-chain robots themselves, ignoring the impact of load. This article proposes a new closed-chain system performance indicator to evaluate the robot configuration. The proposed evaluation indicator effectively considers the influence of load, which is of practical significance to improve the efficiency of task execution. The effectiveness of the proposed index in determining the optimal configuration is demonstrated by simulation verification. In the future, we will focus on multi-arm collaborative operations under a specific configuration.

This study investigates the semi-global fixed-time stability (SGFTS) and global fixed-time stability (GFTS) of nonlinear impulsive systems (NISs). A key challenge in analyzing the SGFTS of such systems lies in the evolving integration methods caused by the impulses. To address this, we dynamically partition the semi-global attraction set (SGAS) and solve the corresponding differential equations within each subset. Additionally, by constructing the transition dynamics of impulse points and iteratively computing these points, we establish the conditions for SGFTS under both stabilizing and destabilizing impulses. For GFTS, the primary difficulty arises from the distinct trajectories and dynamics of points located inside and outside the SGAS. To overcome this, we introduce the concept of the maximum-minimum impulse interval and derive a sufficient condition that ensures the system can enter the SGAS from a distance under a finite number of impulses. Furthermore, we develop a criterion for GFTS under varying impulse degrees and provide convergence time estimation based on the research on SGFTS of NIS. Finally, numerical examples are presented to validate the theoretical results. Notably, in Example 3, a fixed-time impulse controller is designed based on the proposed theoretical framework to achieve global stabilization of complex systems. This example highlights the potential applications of this work in the field of control.

In this contribution, the problem of fixed-time stabilization in multi-weighted complex networks via the novel adaptive pinning nonchattering control based on the linear matrix inequality (LMI) method, as well as its application to image protection is addressed. Different from the traditional methods, a novel fixed-time stable form is proposed and the convergence time is estimated based on beta function. Next, utilizing the designed continuous adaptive control strategy, a sufficient LMI condition is presented to ensure the fixed-time stabilization of multi-weighted complex networks. Furthermore, the novel nonchattering adaptive pinning control protocol is given to guarantee the fixed-time stabilization of the system only by controlling a small number of nodes. Note that a scheme of how to select the number of control nodes is put forward accordingly. Finally, the effectiveness of the proposed method is verified by the actual financial model. Meanwhile, a number of encryption experiments are carried out based on three networks, and the mean and variance of the encryption performance are calculated to show the stability and robustness of image encryption different from the existing research works.

This work explores the fixed-time stabilization of fuzzy uncertain systems based on conditional integral sliding mode control. The difficulties in solving such problems include the integral windup problem and the severe chattering problem when the system converges. Moreover, the design of the traditional fixed-time controller algorithm in the integral sliding mode control becomes complicated. In order to overcome these difficulties: 1) a piecewise function which can bring distant states closer to the sliding surface is considered in the integral function to prevent the integral windup problem, 2) a class of state variable controllers with odd power is designed to solve the chattering problem due to there is no sign function, 3) a fixed-time control algorithm is introduced into the integral function and the controller to guarantee that both the reachability and sliding motion phases are fixed-time stable. Furthermore, based on 1) and 3), an appropriate fixed-time conditional integral sliding mode controller is constructed to ensure the fixed-time reachability of the designed sliding mode surface. Besides, combining 1), 2) and 3), a class of chattering-free fixed-time integral sliding-mode controllers is established to obtain the fixed-time reachability of the sliding mode surface and the fixed-time stability of sliding mode dynamics. This method dramatically reduces the chattering problem and can adjust integral windup. Finally, two numerical simulations are presented to verify the theoretical results, showing the robustness of the designed overshoot factor and the chattering-free scheme for sliding mode control.

This article mainly explores the fixed-time control problem of fuzzy semi-Markov systems with uncertainties and unknown transition rates. Firstly, the T-S fuzzy semi-Markov system is established by using the membership relation of fuzzy logic and Markov probability property. Then, unlike the existing fixed-time control strategies, this work uses a hyperbolic sine function to replace the traditional multiple powers fixed-time control method and construct a novel fixed-time adaptive integral sliding mode control strategy, which reduces the complexity of the controller and adaptive law while optimizing the sliding mode surface and improving the fixed-time convergence performance of the system. Moreover, compared with current methods that require the assumption that the unknown function satisfies the Lipschitz condition or is bounded, the fully connected neural network is introduced to approximate the unknown nonlinear function in the system, improving the intelligence and practicality of the controller. Finally, the theoretical results are verified through numerical simulation, showing the superior performance of achieving fixed-time stability through the proposed control scheme, the gap in the study of fixed-time control using hyperbolic sine functions and fully connected neural networks is filled.

Most land-air amphibious UAVs feature a four-wheel design that limits their adaptability in narrow and uneven spaces. This study proposes the rotor flywheel as a new land-air design that integrates a one-wheel structure and eight-rotor wings for more flexible motion. The dynamics model is then conducted with the Kane method, finding two power-saving self-balance state while rolling. Its controller design highlights the multi-input decoupling approach utilizing feedback, along with the dynamic model-based component to enable efficient control of its intricate operations. Results of simulations and experimental tests have validated the stability and adaptability of the mode-switching and rolling of the robot in ground motion.

Flexure-based scanning stages driven by piezoelectric (PZT) actuator with large stroke, nanoscale precision, and high bandwidth are quite appealing for developing an advanced multiphoton polymerization 3-D nanolithography system. The motivation of this article is to develop a nanopositioning system, which can simultaneously achieve large stroke, high bandwidth, and nanoscale precision to ensure its machining size, efficiency, and accuracy without traditional step-by-step splicing operations. First, anXYnanopositioning stage with millimeter-scale workspace and nanoscale positioning accuracy is designed. Besides, the natural frequency modeling of the nanopositioning stage is conducted by resorting to compliance analysis based on the matrix method, which is validated by a finite-element analysis (FEA). Moreover, linear active disturbance rejection controller (LADRC) is demonstrated that it can be equivalent to a PID controller filtered using a second-order low-pass filter, which theoretically verifies the effectiveness of controlling the nanopositioning stage. In order to complete LADRC’s successful implementation for nanopositioning stage, a novel quantitative one-parameter-tuning method of LADRC is proposed. Finally, a series of trajectory tracking experiments has been carried out to verify the effectiveness and superiority of the proposed nanopositioning stage. The experimental results verify that the large-stroke compliant nanopositioning system has the capability to achieve millimeter stroke, which has reached 1.035 mm$\times \,\,1.035$mm, while the average tracking error is kept within ±100 nm, and the closed-loop bandwidth is achieved up to 32 Hz.Note to Practitioners—With the purpose to effectively improve the performance in terms of stroke, speed, and accuracy for the piezoelectric (PZT)-actuated scanning system, a completely decoupled nanopositioning stage with millimeter-scale travel range is developed and linear active disturbance rejection controller (LADRC) strategy with a novel quantitative one-parameter-tuning method of strategy is proposed. Experimental results indicate that the compliant nanopositioning system has the capability to achieve millimeter stroke, which has reached 1.035 mm$\times \,\,1.035$mm, while the average tracking error of dynamic tracking control of the nanopositioning stage is kept within ±100 nm, and the closed-loop bandwidth is achieved up to 32 Hz. Therefore, the developed nanopositioning system has satisfactory performance for fulfilling advanced large-size multiphoton polymerization 3-D nanolithography task without step-by-step splicing operations. In summary, the potential applications of the proposed large-stroke nanopositioning strategy will be promising.

This article reports the design and validation of a novel predefined-time barrier function adaptive sliding-mode control (PTBFASMC) strategy for robust control of disturbed systems. The PTBFASMC strategy is established by integrating the time base generator along with the barrier function. Unlike existing similar works, the proposed method enables global predefined-time convergence, i.e., the system trajectory returns to the ultimate bound even if an escape occurs at a certain time instant. Besides, the convergence time can be predefined by the user, which is independent of the initial conditions and disturbance. Moreover, the reaching phase is eliminated and the magnitude of initial control output is zero. Another attractive feature of the proposed method lies in that the ultimate bound can be predefined, i.e., the ultimate bound is independent of the upper bound of disturbance. To avoid large control magnitude, a modified control strategy is provided, which extends the proposed scheme to different scenarios. The stability of the control system is demonstrated, and its superiority is verified through numerical simulations and experimental investigations on a piezoelectric actuator.

Restoring the correct masticatory function of broken teeth is the basis of dental crown prosthesis rehabilitation. However, it is a challenging task primarily due to the complex and personalized morphology of the occlusal surface. In this article, we address this problem by designing a new two-stage generative adversarial network (GAN) to reconstruct a dental crown surface in the data-driven perspective. Specifically, in the first stage, a conditional GAN (CGAN) is designed to learn the inherent relationship between the defective tooth and the target crown, which can solve the problem of the occlusal relationship restoration. In the second stage, an improved CGAN is further devised by considering an occlusal groove parsing network (GroNet) and an occlusal fingerprint constraint to enforce the generator to enrich the functional characteristics of the occlusal surface. Experimental results demonstrate that the proposed framework significantly outperforms the state-of-the-art deep learning methods in functional occlusal surface reconstruction using a real-world patient database. Moreover, the standard deviation (SD) and root mean square (RMS) between the generated occlusal surface and the target crown calculated by our method are both less than 0.161 mm. Importantly, the designed dental crown have enough anatomical morphology and higher clinical applicability.

Rotary ultrasonic machining (RUM) is a superior technology to machine hard and brittle materials. Traditionally, the compensation optimization for the RUM system is limited to a single resonant frequency. This article presents a novel double compensation approach for the impedance and frequency regulations of RUM via multiobjective genetic algorithm (MOGA) aiming to achieve the system resonance and monitor the machining process in real time. For this, we first establish the impedance model of the rotary ultrasonic holder (RUH) by adopting the T-type circuit that includes the comprehensive electromagnetic parameters. The obtained impedance model reveals that both frequency mismatch and impedance mismatch exist in the RUM system, causing the low voltage gain and low vibration transmission. To obtain the optimal compensation to match both the frequency and impedance, an optimization model-based MOGA is developed to intelligently search the accurate capacitance values, where the Pareto frontier is employed to visualize the capacitance solution distribution. Moreover, the response feature of the RUH system is attained by using the state-space equation. Detailed comparisons of four compensation topologies show that the series–series (SS) topology offers the optimal performance, which can match both of the frequency and the impedance well, improving the output active power 7.634 times compared to the conventional one. Finally, the validity of the proposed optimization method is confirmed by using both simulations and experiments.Note to Practitioners—This article was motivated by the transmission efficiency and the stability of ultrasonic vibration in the rotary ultrasonic machining (RUM). The matching issue is critical in RUM because the whole system is very complicated with multiple components such as electrical devices, piezoelectric rings, and mechanical horn. In the conventional RUM, the system matching is limited to a single resonant frequency between the piezoelectric transducer and the electrical driver. However, the impedance matching is also important to influence the ultrasonic vibration. The problem of the ultrasonic matching stems from empirical experiences of the engineers’ or simple heuristic rules instead of advanced approaches. On the other hand, optimization-based techniques are viewed as a great success in industrial and engineering applications. With the assistance of our proposed numerical model and the corresponding simulation, we found that the multiobjective genetic algorithm (MOGA) can intelligently search the optimal compensated parameters to achieve the double matching for both the resonant frequency and the impedance in the RUM system. Finally, our experiments prove that the MOGA optimization can attain optimal transmission efficiency for the electrical voltage and current compared with conventional approaches. This significantly benefits the application of the RUM technology in industry, especially for the precision machining of the hard and brittle materials.

Cable-driven segmented manipulators (CDSMs) featured by superior dexterity, light and slender body are excellent candidates for operations in confined environments. However, the stiffness and load capacity of such manipulators have been a challenge due to their structural elasticity. In this paper, we propose an improved mechanism design based on the preliminary work to enhance the linkage accuracy and arm continuity without sacrificing the dexterity, high stiffness and load capacity of CDSM. The manipulator is composed of 4 improved hybrid active-passive linkage segments. Its short and long linkage cables with pretension mechanism are designed to keep equal angles of adjacent joints. An improved separable small driving control box is also designed with both quick release and load mechanism and stroke amplification mechanism. Then the size of control box can still remain small, even the number of segments and the joint limit angles increase. Considering the improved in-segment linkage characteristic, traditional kinematic equations and Jacobian matrix are greatly simplified with Denavit-Hartenberg (D-H) method. Further trajectory tracking planning based on the simplified kinematics solved the Cartesian space planning for task design. Finally, a prototype system is developed to perform the linkage accuracy and comprehensive obstacle avoidance experiments. Experimental results show that the developed hybrid active and passive CDSM has relatively high accuracy and super dexterity.

With a light and slender body, a cable-driven redundant spatial manipulator (CRSM) has flexible manipulability and high maneuverability in confined environment. However, compared with revolute rigid manipulators, such type of manipulators generally has low stiffness and weak load capacity. In this paper, we propose a new mechanism design to improve the stiffness and load capacity without sacrificing the manipulator dexterity and the end-effector accuracy. The manipulator is composed of 3 active-passive-linkage segments and 1 active tool end-effector. Each active-passive segment has 2 degrees of freedom (DOFs) driven by three evenly distributed cables. Pretension mechanism and linkage cables are designed to keep strict equal angles of adjacent joints. A separable control box, which contains all the motors and cable transmission mechanisms is also designed with a quick release-and-lock mechanism. Therefore, the robotic arm can be easily removed and installed. Based on the equal angle characteristic, kinematic equations of manipulator are established with Denavit-Hartenberg (D-H) method and the Jacobian matrix is also simplified. Further analysis of the workspace supplies the guidance for the task design and motion planning. Finally, a prototype system is developed to perform the stiffness and load capacity experiments. Experimental results show that the developed CRSM has relatively high stiffness and load capacity.

Piezoelectric ceramics(PZT)actuator has been widely used in flexure-guided nanopositioning stage because of their high resolution. However, it is quite hard to achieve high-rate precision positioning control because of the complex hysteresis nonlinearity effect of PZT actuator. Thus, an online RELM algorithm with forgetting property(FReOS-ELM) is proposed to handle this issue. Firstly, we adopt regularized extreme learning machine(RELM)to build an intelligent hysteresis model. The training of the algorithm is completed only in one step, which avoids the shortcomings of the traditional hysteresis model based on artificial neural network(ANN) that slow training speed and easy to fall into the local minimum. Then, based on the regularized on-line sequential extreme learning machine(ReOS-ELM), an on-line RELM algorithm with forgetting property(FReOS-ELM) is designed, which can avoid the computational load of ReOS-ELM in the process of adding new data for learning on-line. In the experiment, a real-time voltage signal with varying frequencies and amplitudes is adopted, and the output displacement data of the nanopositioning stage is also acquired and analyzed. The results powerfully verify that the performance of the established hysteresis model based on the proposed FReOS-ELM is satisfactory, which can be used to improve the practical positioning performance for flexure nanopositioning stage.

It is a big challenging issue of avoiding falling into local optimum especially when facing high-dimensional nonseparable problems where the interdependencies among vector elements are unknown. In order to improve the performance of optimization algorithm, a novel memetic algorithm (MA) called cooperative particle swarm optimizer-modified harmony search (CPSO-MHS) is proposed in this paper, where the CPSO is used for local search and the MHS for global search. The CPSO, as a local search method, uses 1-D swarm to search each dimension separately and thus converges fast. Besides, it can obtain global optimum elements according to our experimental results and analyses. MHS implements the global search by recombining different vector elements and extracting global optimum elements. The interaction between local search and global search creates a set of local search zones, where global optimum elements reside within the search space. The CPSO-MHS algorithm is tested and compared with seven other optimization algorithms on a set of 28 standard benchmarks. Meanwhile, some MAs are also compared according to the results derived directly from their corresponding references. The experimental results demonstrate a good performance of the proposed CPSO-MHS algorithm in solving multimodal nonseparable problems.

This paper develops a new elimination mechanism strategy to improve the performance of cooperative particle swarm optimizer with elimination mechanism (CPSO-EM) algorithm which is proposed to extract better vector elements by analyzing features of cooperative particle swarm optimizer (CPSO). The extracting method is simple and has the potential to be improved. The proposed cooperative particle swarm optimizer with improved elimination mechanism (CPSO-IEM) makes two main changes in order to extract useful elements from elimination mechanism (EM) effectively. These changes not only increase the diversity of solution vectors which are stored in EM, but also improve the performance of cooperative particle swarm optimizer (CPSO) which is treated as a basic operator in CPSO-IEM. Experimental studies on a set of test functions show that CPSO-EM exhibits better performance than several other peer algorithms in solving nonseparable multimodal problems.

This paper presents a new particle swarm optimizer (PSO) that called the cooperative particle swarm optimizer with elimination mechanism (CPSO-EM) in an attempt to address the issue of getting trapped into local optimum when solving nonseparable multimodal problems using PSO algorithm. The proposed CPSO-EM builds on the basis of an early cooperative PSO (CPSO-H) that employs cooperative behavior. The CPSO-H and elimination mechanism (EM) memory are incorporated together to obtain CPSO-EM. Experimental studies on a set of test functions show that CPSO-EM exhibits better performance in solving nonseparable multimodal problems than several other peer algorithms.

A spatial 2-RPU&SPR parallel manipulator (PM) with three degrees of freedom (DOF) is proposed in this paper. The architecture of the manipulator is comprised of a moving platform attached to a base through two revolute-prismatic-universal jointed serial linkages and one spherical-prismatic-revolute jointed serial linkage. The prismatic motions of the prismatic joints are considered to be actively actuated. The moving platform of the manipulator has one-translational and two rotational (1T2R) DOFs with respect to the fixed base. The kinematics including forward and inverse position analysis is analyzed. At last, the simulations of position and velocity of the manipulator are made to validate the algorithm.

Recently, 3D printing manipulators have attracted extensive attention since they have become promising tools to perform the practical prototyping and distributed manufacturing tasks. To improve the kinematic accuracy, dexterity and efficiency of 3D printing manipulators, the concept of a 6-DOF hybrid manipulator, consisting of a 3-DOF parallel manipulator and a 3-DOF rotational wrist, is proposed in this paper. According to the requirement of 3D printing movements, a three-prismatic-universal-universal (3-PUU) translational parallel manipulator (TPM) is designed. Several kinematic properties of the 3-PUU TPM under study are investigated, including the inverse and forward kinematic problems, workspace determination, and dexterity. Both the inverse kinematics and forward kinematics solutions are derived in closed form, and Jacobian matrix is derived analytically. Moreover, in view of the physical constraints imposed by mechanical joints, the reachable workspace is determined. Finally, the dexterity characteristic of the 3-PUU TPM is evaluated based on the condition number of its Jacobian matrix.

This paper presents mechanical system dynamics modeling analysis and control of a novel compliant flexure-based micro-parallel positioning stage. The designed microparallel positioning stage consists of a mobile plate, a fixed base, and three limbs with identical kinematic structure. Certain geometric conditions are adopted to make the mobile plate with purely 3 translational degrees of freedoms. Each limb connects the mobile base to the fixed plate through a P (prismatic) joint and two U(universal) joints in sequence, where P joint is the active joint driven by a pair of novel electromagnetic actuators assembled on the fixed base. The prototype of the designed system is fabricated, dynamics model of the manipulator is constructed through Lagrange method and sliding mode controller is designed based on the dynamics model.

In recent years, piezo-actuated micro/nano positioning stages emerge as a significant tool in the nanotechnology. However, the shortcomings of small positioning stroke and hysteresis of piezoelectric actuators have constrained their further development and applications. In this paper, a novel piezo-actuated hydraulic displacement amplifier (PHDA) based on Pascal's law and area differential principle is first proposed aiming to solve the contradictions among positioning stroke, positioning resolution and mechanism dimension in piezo-actuated micro/nano positioning stages. After a series of optimal designs, the proposed PHDA mechanism is fabricated and experimentally tested. In this study, a piezoelectric (PZT) actuator P-840.20 with open-loop travel of 30 μm is employed, the experimental results indicate that the displacement amplification ratio can reach up to 34.6, thus the maximum output displacement can achieve up to around 1.02 mm. Both theoretical derivation and prototype test results testify the well performance of the proposed mechanism. This new amplifier can be widely extended to practical precision manipulation applications in case of large motion range required.

This paper presents the design and analysis of a novel compliant flexure-based micro-parallel positioning stage for micro active vibration isolation application. The stage is constructed with a symmetric structure by employing three parallel PUU legs, a moving platform and a fixed platform. It is driven by 6 electromagnetic actuators and with 3 translational DOFs. The mobility characters of the stage is analyzed and proved via FEA method. The compliance modeling of the stage is conducted by resorting to compliance matrix method, and analytical models for electromagnetic forces are also established, both mechanical structure and electromagnetic model are validated by finite element analysis (FEA) performed with ANSYS. The mechanical structure is analyzed in a multi-physics environmental simulation and electromagnetic actuators are applied in ANSYS too. Both FEA and the analytical models well demonstrate that the movement of the stage is purely translational. The prototype of the designed system is fabricated, preliminary test shows the design is successful. With the parameters designed in the paper, the stage can have large working space, very high resolution and heavy work-load ability as well.

In recent years, robotic bio-manipulation emerges as a hot research topic in the micro/nano technology. In these applications, biological cell microinjection is a focus since it is a critical process for the further biological research such as genetic engineering and pharmacology research. This study aims to develop a novel robotic biomanipulation system combining with the micro-fluidic chip technology to improve the cell manipulation stability and throughput. Two novel flexure-based large-workspace micromanipulators with modified differential lever displacement amplifier (MDLDA) are presented in this paper. After a series of optimal designs and mechanism modeling, the mechanism performances are evaluated by the FEA method. Finally, the proposed micromanipulators are fabricated and visual-servo controlled to perform the practical zebrafish embryos injection task. In this work, two piezoelectric (PZT) actuators P-216.80 (open-loop travel is 120 μm) and one PZT actuator P-840.20 (open-loop travel is 30 μm) are utilized in the compliant mechanisms, the experiment results indicate that the displacement amplification ratios can reach up to 30.6 and 17.6, thus the maximum output displacements can achieve around 3.1273 mm and 0.528 mm, the rotation angle of the left micromanipulator can reach to around 26.5°. Both theoretical derivation and experimental implementation results well verify the advanced performance of the developed system.

Piezodriven flexure-based motion stages, with a large workspace and high positioning precision, are really attractive for the realization of high-performance atomic force microscope (AFM) scanning. In this paper, a modified lever displacement amplifier is proposed for the mechanism design of a novel compliant two-degree-of-freedom (2-DOF) nanopositioning stage, which can be selected to drive in dual modes. Besides, the modified double four-bar parallelogram, P (P denotes prismatic) joints are adopted in designing the flexure limbs. The established models for the mechanical performance evaluation of the stage, in terms of kinetostatics, dynamics, and workspace, are validated by the finite-element analysis. After a series of dimension optimizations carried out through the particle swarm optimization algorithm, a novel active disturbance rejection controller, including the nonlinearity tracking differentiator, the extended state observer, and the nonlinear state error feedback, is proposed to automatically estimate and suppress plant uncertainties arising from the hysteresis nonlinearity, creep effect, sensor noises, and unknown disturbances. The simulation and prototype test results indicate that the first natural frequency of the proposed stage is approximated to be 831 Hz, the amplification ratio in two axes is about 4.2, and the workspace is 119.7 μm × 121.4 μm, while the cross coupling between the two axes is kept within 2%. All the results prove that the developed stage possesses a good property for high-performance AFM scanning.

This paper presents the design of an approximately decoupled XY micro-motion stage, which adopts the double four-bar prismatic joints to transfer linear motions and a proper type of displacement amplifier. The compliance models of the amplifier, the prismatic joints, and the whole stage are established based on the flexibility matrix method. Based on the input compliance model, the amplification ratio is elaborated. The simulation is made by using finite element analysis software, the simulation results show that the input/output of the stage has a very good linearity, the ratio of output displacement to input displacement is 4. The output cross-talk is less than 2% and the parasitic motions of the input points in the other limbs are less than 1.8%, which shows a good decoupling property.

The paper presents the design and analysis of a dexterous micro-gripper with two fingers and each finger has 2-DOF translational movement function. The two fingers can move independently in hundreds of microns' range, and can cooperate with each other to realize complex operation for micro objects. The mobility characteristics and the inverse parallel kinematic model of a single finger are analyzed by resorting to screw theory and compliance and stiffness matrix method, which are validated by finite-element analysis (FEA). Both FEA and the theoretical model have well validated the movement of the fingers moving in translational way, the designed micro gripper can realize a lot of complex functions. Properly selecting the amplification ratio and the stroke of the PZT, we can mount the gripper onto a positioning stage to realize a larger motion range, which will make it be widely used in micro parts assembly and bio-operation systems.

A compliant 2-DOF nanopositioning stage with a novel concept of dual-mode driven is proposed in this paper aiming to improve the scanning performance of the Atomic Force Microscope (AFM). The stage is featured with nanoscale positioning precision, high bandwidth, long scanning range and fully decoupled structure, which can be selected to work in dual working modes. Based upon the matrix method, the discussions in terms of output compliance, input stiffness and dynamics modeling via Lagrange equation have been performed in detail. Moreover, a series of optimal designs have been implemented using Particle Swarm Optimization (PSO) algorithm. The results of the finite-element analysis (FEA) indicate that the first natural frequency is approximated 583 Hz, the amplification ratio in two axes is about 4, thus the maximum scanning range can reach up to around 341 μm × 341 μm without material failure, while the cross-coupling between the two axes is kept within 2%. All the results indicate that the presented mechanism possesses a good performance for high-rate AFM scanning.

This paper presents a novel compliant parallel XY micromotion stage driven by piezoelectric actuators (PZT). With the purpose to obtain complete kinematic decoupling and good stiffness performance, the stage is designed using a symmetric 4-PP structure in which double four-bar flexure is chosen as the prismatic joint. Matrix method is employed to establish the compliance model of the mechanism. Based on the model, dynamic analysis is investigated after static analysis is carried out. The dimensions of the mechanism are optimized using the particle swarm optimization (PSO) algorithm in order to maximize the natural frequencies. Finite-element analysis (FEA) result indicates that the mechanism has an almost linear force-deflection relationship, high first natural frequency (720.52 Hz), and ideal decoupling property. To cope with the nonlinearities such as hysteresis that exists in the PZT, the control system is constructed by a proportional-integral-derivative (PID) feedback controller with a feedforward compensator based on Preisach model. The fabricated prototype has a 19.2 μm × 8.8 μm rectangular workspace with coupling less than 5%. The result of the closed-loop test shows that the XY stage can achieve positioning, tracking and contouring tasks with small errors.

Piezoelectric hysteresis usually relies on the frequency of the input signal. Most of the existing rate-dependent models use a lot of parameters to capture the rate-dependent hysteresis. In this paper, a simple rate-dependent hysteresis model is proposed to describe the frequency dependency effect of a micropositioning stage driven by piezoelectric actuators. This model is extended from an enhanced Coleman-Hodgdon (C-H) model. It has only 9 parameters and exhibits an accuracy better than 97%. The dependencies of the model parameters on the input rate are derived based on open-loop experimental tests. As inverse rate-dependent C-H model is established to construct a feedforward compensation. Experimental results demonstrate the effectiveness of the rate-dependent model over the traditional rate-independent one. The feedforward in conjunction with a PID feedback control is constructed to further attenuate the modeling errors and creep effects. Results show that the combined control scheme suppresses the tracking error by more than 8 times compared to the stand-alone PID control. It provides a sound base of practical control of the micropositioning system for micro/nano scale manipulation.

This paper reports the design and development processes of a totally decoupled flexure-based XYZ parallel-kinematics micropositioning stage with piezoelectric actuation. The uniqueness of the proposed XYZ stage lies in that it possesses both input and output decoupling properties with integrated displacement amplifiers. The input decoupling is realized by actuation isolation using double compound parallelogram flexures with large transverse stiffness, and the output decoupling is implemented by employing two-dimensional (2-D) compound parallelogram flexures. By simplifying each flexure hinge as a two-degree-of-freedom (2-DOF) compliant joint, analytical models of kinematics, statics, and dynamics of the XYZ stage are established and then validated with finite-element analysis (FEA). The derived models are further adopted for optimal design of the stage through particle swarm optimization (PSO), and a prototype of XYZ stage is fabricated for performance tests. The nonsymmetric hysteresis behavior of the piezo-stage is identified with the modified Prandtl-Ishlinskii (MPI) model, and a control scheme combining the inverse model-based feedforward with feedback control is constructed to compensate the plant nonlinearity and uncertainty. Experimental results reveal that a submicron accuracy 1-D and 3-D positioning can be achieved by the system, which confirms the effectiveness of the proposed mechanism and controller design as well.

Tracking a surface via the end-effector of a manipulator is a tough issue, one not only should implement the position and force control, but also monitor and sense the actual contacting state between the end-effector and the object's surface. In this paper, we present an approach integrating the tactile sensing with force-torque information as the feedback to control the manipulator tracking a surface. Hybrid impedance control method is applied to follow both the position and force trajectories. At the same time, the posture of the end-effector is expected to keep horizontal. With the feedback of tactile sensing data such as contact state, contact area and so on, several strategies of tactile sensing feedback are proposed to be included into the control algorithm. Simulations and two groups of real experiments are made using a 5-DOF manipulator equipped with force/torque and tactile sensors to contact with hard and soft board respectively, and the results are compared and analyzed. The effectiveness of the proposed strategies is validated.

This paper presents the design and fabrication process of a new piezoelectrically actuated flexure-based XYZ compliant parallel-kinematics micropositioning stage with totally decoupled properties. The proposed XYZ stage consists of three limbs which are assembled in an orthogonal manner, and it has both input and output decoupling properties. Analytical models for kinematics, statics, and dynamics of the XYZ stage are established, which are validated by finite element analysis performed with ANSYS. Based on the derived models, architectural parameters of the stage are optimized and a prototype is developed for experimental studies. The results not only verify the effectiveness of the conducted optimum design but also confirm the well-decoupled performance of the XYZ stage, which will be used to execute micro-/nanomanipulation tasks.

In this paper, a global sliding mode control (GSMC) scheme is implemented on a piezo-driven XY parallel micropositioning stage to compensate for the unmodeled hysteresis aiming at a sub-micron accuracy motion tracking control. The GSMC controller is designed with the consideration of all uncertainty bounds. In the controller implementation, a high-gain velocity observer is adopted to estimate the feedback velocity from the measured position. The effectiveness of the GSMC over ordinary SMC and traditional PID control is demonstrated through simulations, while the variations of design parameters on control performances are examined as well. Results show that the GSMC can reduce the hysteresis to a negligible level and lead to a sub-micron accuracy tracking with tolerance to some degrees of external disturbances, which provides a sound base of practical control of the micropositioning system for micro/nano scale manipulation.

In recent years, many applications in precision engineering require a careful isolation of the instrument from the vibration sources by adopting active vibration isolation system to achieve a very low remaining vibration level especially for the very low frequency under 10Hz vibration signals. In this paper, based on the previous research experiences in the systematical modeling and study of parallel robots, a hybrid robot is described and the vibration model is given by using Lagrange's equations. Then the present study addresses the issues related to the active vibration control schemes for the MIMO system using LQR algorithm. Finally, numerical simulations on the effect of active vibration control are presented.

This paper presents a complete design and development procedure of a new XY micromanipulator for two-dimensional (2-D) micromanipulation applications. The manipulator possesses both a nearly decoupled motion and a simple structure, which is featured with parallel-kinematic architecture, flexure hinge-based joints, and piezoelectric actuation. Based on pseudo-rigid-body (PRB) simplification approach, the mathematical models predicting kinematics, statics, and dynamics of the XY stage have been obtained, which are verified by the finite-element analysis (FEA) and then integrated into dimension optimization via the particle swarm optimization (PSO) method. Moreover, a prototype of the micromanipulator is fabricated and calibrated using a microscope vision system, and visual servo control employing a modified PD controller is implemented for the accuracy improvement. The experiments discover that a workspace size of 260 mum times 260 mum with a 2-D positioning accuracy and repeatability around 0.73 and 1.02 mum, respectively, can be achieved by the micromanipulator.

In this paper, a concept of totally decoupling is proposed for the design of a flexure parallel micromanipulator with both input and output decoupling. Based on flexure hinges, the design procedure for an XY totally decoupled parallel stage (TDPS) is presented, which is featured with decoupled actuation and decoupled output motion as well. By employing (double) compound parallelogram flexures and a compact displacement amplifier, a class of novel XY TDPS with simple and symmetric structures are enumerated, and one example is chosen for further analysis. The kinematic and dynamic modeling of the manipulator are conducted by resorting to compliance and stiffness analysis based on the matrix method, which are validated by finite-element analysis (FEA). In view of predefined performance constraints, the dimension optimization is carried out by means of particle swarm optimization, and a prototype of the optimized stage is fabricated for performance tests. Both FEA and experimental studies well validate the decoupling property of the XY stage that is expected to be adopted into micro-/nanoscale manipulations.

This paper presents the design and development procedures of a new decoupled XY micromanipulator for micro scale positioning applications. The manipulator is featured with parallel-kinematic architecture, flexure hinge-based joints, and piezoelectric actuation. Based on the lumped model, the efficient models for kinematics, statics and dynamics of the XY stage have been obtained, which are verified by resorting to the finite element analysis via ANSYS software package. Moreover, the stage dimensions are optimized through the particle swarm optimization (PSO) approach, and a manipulator with performances satisfying the requirements is generated. Furthermore, a prototype of the manipulator has been fabricated via the wire-EDM process. The developed micromanipulator is expected to be adopted in practical applications.

The design procedure for a totally decoupled XY flexure parallel kinematic manipulator is presented in this paper. The designed XY stage is featured with flexure hinges and a relatively simple structure. The output decoupling is allowed by the employment of compound parallelogram flexure, and the input decoupling is implemented by actuation isolation which is enabled by the double compound parallelogram flexure with large transverse stiffness. An improved displacement amplifier is adopted to amplify the stroke of linear actuator and to simplify the stage architecture. Kinematic models of both the amplifier and the XY stage are conducted by resorting to compliance analysis based on matrix method, which are validated by finite element analysis performed with ANSYS. The presented results are helpful for the design of a new XY flexure parallel manipulator for micro/nano scale manipulation.

Particle swarm optimization (PSO) is a population-based stochastic recursion procedure, which simulates the social behavior of a swarm of ants or a school of fish. Based upon the general representation of individual particles, this paper introduces a decreasing coefficient to the updating principle, so that PSO can be viewed as a regular stochastic approximation algorithm. To improve exploration ability, a random velocity is added to the velocity updating in order to balance exploration behavior and convergence rate with respect to different optimization problems. To emphasize the role of this additional velocity, the modified PSO paradigm is named PSO with controllable random exploration velocity (PSO-CREV). Its convergence is proved using Lyapunov theory on stochastic process. From the proof, some properties brought by the stochastic components are obtained such as "divergence before convergence" and "controllable exploration." Finally, a series of benchmarks is proposed to verify the feasibility of PSO-CREV.

A novel design of a mobile parallel manipulator (MPM), which is composed by a multi-degree of freedom (DOF) parallel robot and an autonomous wheeled mobile platform, is proposed in this paper to overcome the shortcomings of the parallel robot and perform high accuracy tasks. Both the position and differential kinematics problems for the hybrid system are solved in details, and the dynamic model for the MPM is derived via Lagrangian formulation approach with simplifying hypotheses. Furthermore, taking the MPM self motion into consideration due to its redundancy, the dynamic control in task space is implemented by employing a model-based controller. Simulation results illustrate that not only the control algorithms are effective well, but also the established dynamic models are accurate enough as well

It is a challenging task for multiple robots working together to realize object transportation. This paper studies a practical situation that a group of mobile manipulators are used to transport an object whose mass can not be ignored. From the viewpoint of formation, a leader-follower type control is designed. To overcome parameter uncertainty in modeling robot, a decentralized control law is applied to individual robots, in which an adaptive NN is used to model robot dynamics online. Using Lyapunov theory, we have proved that if all end-effectors of robots will keep proper relative distances with a regular formation to manipulate a heavy object, the object will be transported to the destination at last. But due to parameter uncertainties, there may exist a static position error, which can be reduced by proper selection of control coefficients.

This paper addresses the multiple tasks performing issues for redundant nonholonomic mobile manipulators. An extended gradient projection redundancy resolution scheme is proposed which can determine the directions of self-motion to perform multiple secondary tasks. This scheme is easy to use and can avoid algorithm singularities. A general dynamic modeling method is presented in consideration of nonholonomic constraints, interactive motions and self-motions. A real-time fuzzy logic self-motion planner is devised to create desired self-motion magnitudes and a robust adaptive neural-network controller is designed to accomplish multiple secondary tasks without affecting the primary one in the workspace. The effectiveness of the proposed algorithm is verified through simulations for a 3DOF manipulator atop a 3-wheeled mobile platform system

The stiffness modeling for a compliant parallel manipulator (CPM) is very important since it provides a basis for the characterization of static, modal, and dynamic behavior of the CPM. This paper presents the stiffness modeling of a three-prismatic-revolute-cylindrical (3-PRC) CPM with orthogonally mounted actuators, that is designed to provide three spatial translational DOF for nano scale manipulation. A straightforward method is developed to establish the analytical stiffness model for a spatial CPM by considering the compliance of each compliant element, which is then applied to stiffness modeling of the 3-PRC CPM. Furthermore, the finite element analysis is carried out to validate the developed model. And to demonstrate the utility of the stiffness model, the influence of architectural parameters on stiffness factors is analyzed, which is valuable for a cost-effective design of the CPM

A new 2-degrees of freedom compliant parallel micromanipulator (CPM) utilizing flexure joints is proposed for two-dimensional nanomanipulation in this paper. By a proper selection of actuators, flexure hinges, and materials, this system is constructed and analyzed by a pseudorigid-body model, architectural optimization, and finite-element analysis. Both the position and velocity kinematic modelings are established, and afterwards, statics analysis is performed. In view of the physical constraints imposed by pizeo-actuators and flexure hinges, the CPM's workspace area is determined. And in order to achieve a maximum workspace subjected to the given dexterity indices, kinematic optimization of the design parameters is carried out, which results in a manipulator satisfying the operational requirements. Furthermore, the finite-element analysis has been undertaken to validate the analytical modeling, and the influence of architectural parameters on CPM performance has been evaluated as well. Note to Practitioners-This paper is motivated by the problem of designing a nanomanipulator for two-dimensional (2-D) assembly of nanoscale objects via nanomanipulation. A novel planar parallel mechanism incorporating compliant mechanisms is designed for such a purpose. Since the application of the manipulator depends significantly on the kinematic mathematical models, the designed compliant parallel micromanipulator (CPM) is analyzed by the established pseudorigid-body (PRB) model. The architectural optimization leads to a CPM satisfying the workspace and resolution requirements of this work. Moreover, finite-element analysis is performed to verify the accuracy of the developed PRB model, and simulation results illustrate the efficiency of the PRB model in designing and analyzing the CPM. Since the designed CPM is composed solely of flexural elements which are known to be competent in high precise applications, it is reasonable to expect that the CPM could find its way into 2-D manipulation of nanoscale components.

A new three degrees of freedom translational parallel manipulator (TPM) with fixed actuators, called a general 3-PRC TPM, is proposed in this paper. The mobility of the manipulator is analyzed via screw theory. The inverse kinematics, forward kinematics, and velocity analysis are performed and the singularity problems are investigated afterwards, which can be applied to a general 3-PRC TPM regardless of actuators arrangement. With the variation on actuators layout angle, the reachable workspace of the manipulator is generated and compared. Especially, it is illustrated that the manipulator in principle possesses a uniform workspace with a constant hexagon shape cross section. Furthermore, the dexterity characteristics is investigated in the global sense. Simulation results show that different specific tasks should be considered when the actuators layout angles of a general 3-PRC TPM are designed.

The formation task achieved by multiple robots is a tough issue because of the limitations of the sensing abilities and communicating functions among them. Due to an individual robot can only handle local information, an adjacency graph is applied to describe the relationship among multiple robots. Since the relative positions among robots change from time to time, the topology graph describing information exchange is variant. A local control strategy is proposed for an individual robot based on NN control with robust terms. It has been proved that under an assumption of adjacency matrices associated with interaction graph being always connected, the system will converge based on the individual control strategy and multiple robots can construct an unique formation even if interaction topology is variant.

This paper presents a new algorithm for automatic overturn prevention and path following control of redundant nonholonomic mobile modular manipulators. According to modular robot concept, a new dynamic modeling method is proposed in consideration of interactive motions, nonholonomic constraints and self-motions. Then, an online self-motion planner (SMP) and a robust adaptive neural-fuzzy controller (RANFC) are devised; the former is used to generate desired self-motions in a real-time manner, while the latter is used to prevent the robot from overturning and to control the end-effector to follow a desired spacial trajectory at the same time. The proposed algorithm does not need exact apriori knowledge of dynamic parameters and can suppress bounded external disturbance effectively. Simulation results for a real robot demonstrate that the proposed algorithm is effective.

The concept of a medical robot constructed by parallel mechanisms for chest compressions in rescuing a patient is proposed in this paper. In light of the requirements of cardiopulmonary resuscitation (CPR) from medical aspects, a new translational parallel manipulator (TPM) employing the architecture of a modified version of DELTA parallel robot is designed, which utilizes an architectural optimization methodology for such applications. The mobility and velocity analysis of the manipulator is carried out in details. By introducing a simplifying hypothesis, the inverse dynamic modeling is performed based upon the principle of virtual work. Moreover, the dynamic control using computed torque method is implemented, and simulation results illustrate the well performance of the control algorithm. The research works lay a sound foundation on developing a medical robot prototype to assist in CPR operation.

The joint parameters of redundant manipulators are prerequisite data for effective dynamics control. An identification method via fuzzy theory and Genetic Algorithm has been presented to study modular redundant robots. The Genetic Algorithm is used in the fuzzy optimization expecting to obtain global optimal solutions. Experimental modal analysis and Finite Element Method have been exploited in dynamics modeling. The joint parameters of a 9-DOF modular redundant robot have been identified. Active vibration control has been approached to a simplified 4-DOF modular manipulator by DOF reduction to the 9-DOF modular manipulator.