Publications

Integral resonant damping for high-bandwidth control of piezoceramic stack actuators with asymmetric hysteresis nonlinearity

This paper presents a novel control scheme for high-bandwidth control of piezoceramic stack actuators (PSAs). For this purpose, we first characterize and compensate for the asymmetric hysteresis nonlinearity of the PSA. A linear integral resonant controller is then designed as a means for damping the resonant modes of the dynamic system with the hysteresis compensation. Finally, a tracking controller and feedforward input are developed to minimize the tracking errors and improve the closed-loop tracking bandwidth. To verify the effectiveness and efficiency of the proposed control scheme, a PSA-actuated positioning platform is built and comparative experiments are conducted. Experimental results demonstrate that the proposed controller achieves robust broadband nanopositioning of the PSA by improving the tracking bandwidth from 22Hz (with an integral controller) to 657Hz.

Kinetostatic Modeling and Position-Orientation Control of Bellow-Shaped Soft Continuum Robots

Bellow-shaped soft continuum robots with parallel mechanisms feature an excellent balance between structural stiffness and contact compliance, making them highly promising in various applications. However, their complex structures and nonlinear elastic characteristics pose significant challenges in modeling and control. In this work, we propose a kinetostatic model and a corresponding position-orientation controller for bellow-shaped soft continuum robots. First, bellow-shaped soft actuators are simplified into hyperelastic cylinder soft actuators with mechanical equivalence. In addition, the overall deformation is decoupled into elongation and bending components to enhance computational efficiency. Based on these two simplifying strategies, the kinetostatic model is developed with absolute nodal coordinate formulation theory. Then, forward and inverse kinetostatic mappings are defined, and the numerical solution algorithm is presented. Finally, the developed model is experimentally validated through configuration simulation and feedforward trajectory tracking. Experimental results demonstrate that the developed model achieves low prediction errors, with configuration simulation errors of 3.43%. Furthermore, with the model-based feedforward controller, a two-segment soft continuum robot can accurately follow desired trajectories with specified bending angles, achieving average position and angle errors of 4.14 mm and 1.58<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula>, respectively.

Soft Actuators and Robots Enabled by Additive Manufacturing

Soft robotic systems are human friendly and can mimic the complex motions of animals, which introduces promising potential in various applications, ranging from novel actuation and wearable electronics to bioinspired robots operating in unstructured environments. Due to the use of soft materials, the traditional fabrication and manufacturing methods for rigid materials are unavailable for soft robots. 3D printing is a promising fabrication method for the multifunctional and multimaterial demands of soft robots, as it enables the personalization and customization of the materials and structures. This review provides perspectives on the manufacturing methods for various types of soft robotic systems and discusses the challenges and prospects of future research, including in-depth discussion of pneumatic, electrically activated, magnetically driven, and 4D-printed soft actuators and integrated soft actuators and sensors. Finally, the challenges of realizing multimaterial, multiscale, and multifunctional 3D-printed soft robots are discussed.

Fabric-based cellular pneumatic actuators with programmable shape morphing and high stiffness variation for soft wearable robots

Intelligent Robotics and Applications

No abstract is provided for this article.

Robust adaptive control of a class of nonlinear systems with inverse compensation of unknown asymmetrical backlash nonlinearity

This paper deals with the robust inverse compensation and control for a class of nonlinear systems with unknown asymmetric input backlash. With an analytical expression of the inverse compensation error, a corresponding controller is designed by using the robust adaptive control approach. The developed control law ensures global stability of the whole control system and achieves both stabilization and tracking with desired precision. Simulations performed on an unstable uncertain nonlinear system illustrate and clarify the approach.

Soft robotic hand with tactile palm-finger coordination

Soft robotic hands with integrated sensing capabilities hold great potential for interactive operations. Previous work has typically focused on integrating sensors with fingers. The palm, as a large and crucial contact region providing mechanical support and sensory feedback, remains underexplored due to the currently limited sensing density and interaction with the fingers. Here, we develop a sensorized robotic hand that integrates a high-density tactile palm, dexterous soft fingers, and cooperative palm-finger interaction strategies. The palm features a compact visual-tactile design to capture delicate contact information. The soft fingers are designed as fiber-reinforced pneumatic actuators, each providing two-segment motions for multimodal grasping. These features enable extensive palm-finger interactions, offering mutual benefits such as improved grasping stability, automatic exquisite surface reconstruction, and accurate object classification. We also develop palm-finger feedback strategies to enable dynamic tasks, including planar object pickup, continuous flaw detection, and grasping pose adjustment. Furthermore, our development, augmented by artificial intelligence, shows improved potential for human-robot collaboration. Our results suggest the promise of fusing rich palm tactile sensing with soft dexterous fingers for advanced interactive robotic operations. Robotic hands with tactile sensing hold potential for interactive operations, yet palm sensing remains underexplored. Here, authors present a robotic hand that integrates a high-density tactile palm with soft, dexterous fingers, enhancing palm-finger coordination for improved robotic operation and perception.

Motion Control of Piezoelectric Positioning Stages: Modeling, Controller Design, and Experimental Evaluation

In this paper, a general skeleton on modeling, controller design, and applications of the piezoelectric positioning stages is presented. Toward this framework, a general model is first proposed to characterize dynamic behaviors of the stage, including frequency response of the stage, voltage-charge hysteresis and nonlinear electric behavior. To illustrate the validity of the proposed general model, a dynamic backlash-like model is adopted as one of hysteresis models to describe the hysteresis effect, which is confirmed by experimental tests. Thus, the developed model provides a general frame for controller design. As an illustration to this aspect, a robust adaptive controller is developed based on a reduced dynamic model under both unknown hysteresis nonlinearities and parameter uncertainties. The proposed control law ensures the boundedness of the closed-loop signals and desired tracking precision. Finally, experimental tests with different motion trajectories are conducted to verify the proposed general model and the robust control law. Experimental results demonstrate the excellent tracking performance, which validates the feasibility and effectiveness of the proposed approach.

Modeling the Viscoelastic Hysteresis of Dielectric Elastomer Actuators with a Modified Rate-Dependent Prandtl–Ishlinskii Model

Dielectric elastomer actuators (DEAs) are known as a type of electric-driven artificial muscle that have shown promising potential in the field of soft robotics. However, the inherent viscoelastic nonlinearity makes the modeling and control of DEAs challenging. In this paper, we propose a new phenomenological modeling approach with the Prandtl–Ishlinskii (P–I) model to characterize the viscoelastic hysteresis nonlinearity of DEAs. Differently from the commonly used physics-based models, the developed phenomenological model, called the modified rate-dependent P–I model (MRPIM), produces behavior similar to that of physics-based models but without necessarily considering physical insight into the modeling problem. In this way, the developed MRPIM can characterize the asymmetric and rate-dependent viscoelastic hysteresis with a relative simple mathematical format using only the experimental data. To validate the development, experimental tests were conducted with seven different frequencies; four were selected to identify the model parameters and the rest of the data were used to further verify the model. Comparisons between the model prediction and experimental data demonstrate that the MRPIM can precisely describe the viscoelastic hysteresis effect of DEAs with a maximum prediction error of 9.03% and root-mean-square prediction error of 4.50%.

3D Printable High Performance Conducting Polymer Hydrogel for All-Hydrogel Bioelectronics

Owing to the unique combination of electrical conductivity and tissue-like mechanical properties, conducting polymer hydrogels have emerged as a promising candidate for bioelectronic interfacing with biological systems. However, despite the recent advances, the development of hydrogels with both excellent electrical and mechanical properties in physiological environments remains a lingering challenge. Here, we report a bi-continuous conducting polymer hydrogel (BC-CPH) that simultaneously achieves high electrical conductivity (over 11 S cm -1 ), stretchability (over 400%) and fracture toughness (over 3,300 J m -2 ) in physiological environments, and is readily applicable to advanced fabrication methods including 3D printing. Enabled by the BC-CPH, we further demonstrate multi-material 3D printing of monolithic all-hydrogel bioelectronic interfaces for long-term electrophysiological recording and stimulation of various organs. This study may offer promising materials and a platform for future bioelectronic interfacing.

3D-printed PEDOT:PSS for soft robotics

No abstract is provided for this article.

MC-Tac: Modular Camera-Based Tactile Sensor for Robot Gripper

No abstract is provided for this article.

Look-to-Touch: A Vision-Enhanced Proximity and Tactile Sensor for Distance and Geometry Perception in Robotic Manipulation

Camera-based tactile sensors provide robots with a high-performance tactile sensing approach for environment perception and dexterous manipulation. However, achieving comprehensive environmental perception still requires cooperation with additional sensors, which makes the system bulky and limits its adaptability to unstructured environments. In this work, we present a vision-enhanced camera-based dual-modality sensor, which realizes full-scale distance sensing from 50 cm to -3 mm while simultaneously keeping ultra-high-resolution texture sensing and reconstruction capabilities. Unlike conventional designs with fixed opaque gel layers, our sensor features a partially transparent sliding window, enabling mechanical switching between tactile and visual modes. For each sensing mode, a dynamic distance sensing model and a contact geometry reconstruction model are proposed. Through integration with soft robotic fingers, we systematically evaluate the performance of each mode, as well as in their synergistic operation. Experimental results show robust distance tracking across various speeds, nanometer-scale roughness detection, and sub-millimeter 3D texture reconstruction. The combination of both modalities improves the robot's efficiency in executing grasping tasks. Furthermore, the embedded mechanical transmission in the sensor allows for fine-grained intra-hand adjustments and precise manipulation, unlocking new capabilities for soft robotic hands.

Design and analysis of a high-speed XYZ nanopositioning stage

This paper presents the design and analysis of a high-speed XYZ nanopositioning stage. The developed stage is composed of a parallel-kinematic XY stage and a Z stage which is nested within the end-effector of the XY stage. To achieve high resonance frequencies, four special flexure modules with large stiffness are employed for the XY stage. These modules are arranged symmetrically to reduce cross-coupling between X- and Y-axis. For the Z stage, a symmetrical leaf flexure parallelogram mechanism is adopted, which has high resonance frequencies and no cross-coupling. Static and dynamic analysis are performed respectively to establish analytical models for the developed XYZ stage. Based on these models, the dimensions of the stage are optimized to maximize the first resonance frequency of the X-and Y-axis. Then, finite-element analysis (FEA) is conducted to validate the performance of the developed XYZ nanopositioning stage. The FEA results reveal that the workspace of the stage is 9.2 μm × 9.2 μm × 3.1 pm and the first resonance frequencies of the stage in three axes are 7.3 kHz, 7.3 kHz and 46.2 kHz, respectively, which agrees with the analytical results.

Soft multifunctional bistable fabric mechanism for electronics-free autonomous robots

Pneumatic soft robots are promising in diverse applications while they typically require additional electronics or components for pressure control. Fusing pneumatic actuation and control capabilities into a simple soft module remains challenging. Here, we present a class of bistable fabric mechanisms (BFMs) that merge soft bistable actuators and valves for electronics-free autonomous robots. The BFMs comprise two bonding fabric chambers with embedded tubes, where the straightening of one chamber compels the other to buckle for the bistability of the structure and the switching of the tube kinking. Our BFMs can facilitate fast bending actuation (more than 1166° s −1 ), on/off and continuous pressure regulation, pneumatic logic computations, and autonomous oscillating actuation (up to 4.6 Hz). We further demonstrate the capabilities of BFMs for diverse robotic applications powered by one constant-pressure air supply: a soft gripper for dynamic grasping and a soft crawler for autonomous jumping. Our BFM development showcases unique features and huge potential in advancing entirely soft, electronics-free autonomous robots.

Modeling and control of a dielectric elastomer actuator

The emerging field of soft robotics offers the prospect of applying soft actuators as artificial muscles in the robots, replacing traditional actuators based on hard materials, such as electric motors, piezoceramic actuators, etc. Dielectric elastomers are one class of soft actuators, which can deform in response to voltage and can resemble biological muscles in the aspects of large deformation, high energy density and fast response. Recent research into dielectric elastomers has mainly focused on issues regarding mechanics, physics, material designs and mechanical designs, whereas less importance is given to the control of these soft actuators. Strong nonlinearities due to large deformation and electromechanical coupling make control of the dielectric elastomer actuators challenging. This paper investigates feed-forward control of a dielectric elastomer actuator by using a nonlinear dynamic model. The material and physical parameters in the model are identified by quasi-static and dynamic experiments. A feed-forward controller is developed based on this nonlinear dynamic model. Experimental evidence shows that this controller can control the soft actuator to track the desired trajectories effectively. The present study confirms that dielectric elastomer actuators are capable of being precisely controlled with the nonlinear dynamic model despite the presence of material nonlinearity and electromechanical coupling. It is expected that the reported results can promote the applications of dielectric elastomer actuators to soft robots or biomimetic robots.

An experimental comparison of proportional-integral, sliding mode, and robust adaptive control for piezo-actuated nanopositioning stages

This paper presents a comparative study of the proportional-integral (PI) control, sliding mode control (SMC), and robust adaptive control (RAC) for applications to piezo-actuated nanopositioning stages without the inverse hysteresis construction. For a fair comparison, the control parameters of the SMC and RAC are selected on the basis of the well-tuned parameters of the PI controller under same desired trajectories and sampling frequencies. The comparative results show that the RAC improves the tracking performance by 17 and 37 times than the PI controller in terms of the maximum tracking error em and the root mean tracking error erms, respectively, while the RAC improves the tracking performance by 7 and 9 times than the SMC in terms of em and erms, respectively.

Fast‐Response, Stiffness‐Tunable Soft Actuator by Hybrid Multimaterial 3D Printing

Soft robots have the appealing advantages of being highly flexible and adaptive to complex environments. However, the low‐stiffness nature of the constituent materials makes soft robotic systems incompetent in tasks requiring relatively high load capacity. Despite recent attempts to develop stiffness‐tunable soft actuators by employing variable stiffness materials and structures, the reported stiffness‐tunable actuators generally suffer from limitations including slow responses, small deformations, and difficulties in fabrication with microfeatures. This work presents a paradigm to design and manufacture fast‐response, stiffness‐tunable (FRST) soft actuators via hybrid multimaterial 3D printing. The integration of a shape memory polymer layer into the fully printed actuator body enhances its stiffness by up to 120 times without sacrificing flexibility and adaptivity. The printed Joule‐heating circuit and fluidic cooling microchannel enable fast heating and cooling rates and allow the FRST actuator to complete a softening–stiffening cycle within 32 s. Numerical simulations are used to optimize the load capacity and thermal rates. The high load capacity and shape adaptivity of the FRST actuator are finally demonstrated by a robotic gripper with three FRST actuators that can grasp and lift objects with arbitrary shapes and various weights spanning from less than 10 g to up to 1.5 kg.