Dexterous Movements Research Articles

Ultra-Tough, yet Rigid and Healable Supramolecular Polymers with Variable Stiffness for Multimodal Actuators.

Variable stiffness materials have shown considerable application in soft robotics. However, previously reported materials often struggle to reconcile high stiffness, stretchability, toughness, and self-healing ability, because of the inherently conflicting requisite of these properties in molecular design. Herein, we propose a novel strategy that involves incorporating acid-base ionic pairs capable of from strong crosslinking sites into a dense and robust hydrogen-bonding network to construct rigid self-healing polymers with tunable stiffness and excellent toughness. To demonstrate these distinct features, the polymer was employed to serve as the strain-regulation layers within a fiber-reinforced pneumatic actuator (FPA). The exceptional synergy between the configuration versatility of FPA and the dynamic molecular behavior of the supramolecular polymers equips the actuator with simultaneous improvement in motion dexterity, multimodality, loading capacity, robustness, and durability. Additionally, the concept of integrating high dexterity at both macro- and micro-scale is prospective to inspire the design of intelligent yet robust devices across various domains.

Molecular and Cellular Mechanisms of Motor Circuit Development.

Motor circuits represent the main output of the central nervous system and produce dynamic behaviors ranging from relatively simple rhythmic activities like swimming in fish and breathing in mammals to highly sophisticated dexterous movements in humans. Despite decades of research, the development and function of motor circuits remain poorly understood. Breakthroughs in the field recently provided new tools and tractable model systems that set the stage to discover the molecular mechanisms and circuit logic underlying motor control. Here, we describe recent advances from both vertebrate (mouse, frog) and invertebrate (nematode, fruit fly) systems on cellular and molecular mechanisms that enable motor circuits to develop and function and highlight conserved and divergent mechanisms necessary for motor circuit development.

Finger-specific effects of age on tapping speed and motor fatigability.

Increased motor fatigability is a symptom of many neuromuscular and neurodegenerative disorders. However, it is difficult to pinpoint pathological motor fatigability, since the phenomena has not yet been fully characterized in the healthy population. In this study, we investigate how motor fatigability differs across age. Given that many disorders involve supraspinal components, we characterize motor fatigability with a paradigm that has previously been associated with supraspinal mechanisms. Finger tapping at maximal speed results in a rapid decrease in movement speed, which is a measure of motor fatigability. We collected finger tapping data in a field experiment from the general population with a smartphone app, and we investigated age differences in maximal tapping speed, as well as the decrease in tapping speed for the index, middle, and little fingers. We found that the maximal tapping speed differed significantly between young (18-30 years, n = 194) and aged (50-70 years, n = 176), whereas the fatigability-induced relative decrease in movement speed did not differ between the age groups (average decrease: 17.0% ± 6.9% (young) vs. 16.5% ± 7.5% (aged) decrease). Furthermore, tapping speed and motor fatigability depended on which finger was used. These findings might relate to dexterity, with more dexterous movements being more resistant to fatigue. In this study, we provide a characterization of motor fatigability in the general population which can be used as a comparison for clinical populations in the future.

Ultra‐Tough, yet Rigid and Healable Supramolecular Polymers with Variable Stiffness for Multimodal Actuators

AbstractVariable stiffness materials have shown considerable application in soft robotics. However, previously reported materials often struggle to reconcile high stiffness, stretchability, toughness, and self‐healing ability, because of the inherently conflicting requisite of these properties in molecular design. Herein, we propose a novel strategy that involves incorporating acid‐base ionic pairs capable of from strong crosslinking sites into a dense and robust hydrogen‐bonding network to construct rigid self‐healing polymers with tunable stiffness and excellent toughness. To demonstrate these distinct features, the polymer was employed to serve as the strain‐regulation layers within a fiber‐reinforced pneumatic actuator (FPA). The exceptional synergy between the configuration versatility of FPA and the dynamic molecular behavior of the supramolecular polymers equips the actuator with simultaneous improvement in motion dexterity, multimodality, loading capacity, robustness, and durability. Additionally, the concept of integrating high dexterity at both macro‐ and micro‐scale is prospective to inspire the design of intelligent yet robust devices across various domains.

Comparative Analysis of Structure and Motion of Vision Logistics Robotic Arms

This paper combines visual recognition and robotic arm, optimizes the design of robotic arm structure, and researches the logistics robotic arm with six degrees of freedom and visual perception ability to enrich the logistics robotic use scene. Firstly, the visual recognition system is installed on the existing six-degree-of-freedom robotic arm, and the coordinate system is established by the light bar recognition method combined with the D-H parameter method. Secondly, a kinematic simulation model was established by using MATLAB, and the state of the joints was analyzed by using forward and inverse kinematic simulation and fifth degree polynomial interpolation. Finally, the actual logistics fixed-point transportation task is designed for trajectory planning. The results show that the robotic arm is able to be able to perform different grasping tasks in non-structural environments, around the visual analysis of the robotic arm as well as the optimization of the motion track, to enhance the efficiency of the comprehensive use of visual and tactile information, to improve the adaptability of the robotic hand grasping, and to be able to meet the precise control of the pick-up process and the use of the realization of the payload grasping and dexterous movement. The research in this paper provides a certain reference value for the propulsion robot arm to perform intelligent grasping tasks.

Voxel Design of Grayscale DLP 3D-Printed Soft Robots.

Grayscale digital light processing (DLP) printing is a simple yet effective way to realize the variation of material properties by tuning the grayscale value. However, there is a lack of available design methods for grayscale DLP 3D-printed structures due to the complexities arising from the voxel-level grayscale distribution, nonlinear material properties, and intricate structures. Inspired by the dexterous motions of natural organisms, a design and fabrication framework for grayscale DLP-printed soft robots is developed by combining a grayscale-dependent hyperelastic constitutive model and a voxel-based finite-element model. The constitutive model establishes the relationship between the projected grayscale value and the nonlinear mechanical properties, while the voxel-based finite-element model enables fast and efficient calculation of the mechanical performances with arbitrarily distributed material properties. A multiphysics modeling and experimental method is developed to validate the homogenization assumption of the degree of conversion(DoC) variation in a single voxel. The design framework is used to design structures with reduced stress concentration and programmable multimodal motions. This work paves the way for integrated design and fabrication of functional structures using grayscale DLP 3Dprinting.

Force-position collaborative optimization of rope-driven snake manipulator for capturing non-cooperative space targets

With the rapid development of space activities, non-cooperative space targets increase swiftly, such as failed satellites and upper stages, threating normal spacecrafts seriously. As there are some problems in the capture process, such as excessive collision and fast tumbling of targets, manipulator with redundant Degrees of Freedom (DOFs) can be used to improve the compliance and therefore solve these problems. The Rope-Driven Snake Manipulator (RDSM) is a combination of hyper-redundant DOFs and better compliance, and therefore it is suitable for capturing mission. In this paper, a snake manipulator mechanism is designed, and the complete kinematic model and system dynamic model considering RDSM, target and contact is established. Then, to obtain the configuration of joint with hyper-redundant DOFs, an improved motion dexterity index is proposed as the joint motion optimization target. Besides, the force-position collaborative optimization index is designed to adjust active stiffness, and the impedance control method based on the modified index is used to capture the space target. Finally, the proposed force-position collaborative optimization method is verified by virtual prototype co-simulation. The results demonstrate that based on the proposed method, the collision force is reduced by about 25% compared to normal impedance control, showing higher safety.

Exploring Kinematic Bifurcations and Hinge Compliance for In‐Hand Manipulation: How Could Thick‐Panel Origami Contribute?

Origami‐inspired mechanisms have found significant applications in end effector design. So far, the exploration of thick‐panel origami has been relatively limited, but it is worth noting that the incorporation of rigid thick panels can introduce unique mechanical properties, showcasing great potential in addressing manipulation challenges. Our previous work has developed a gripper from thick‐panel waterbomb origami, which can pick up a variety of daily objects. Based on the same prototype, this article extends the gripper's function from grasping to in‐hand manipulation, which is attributed to the kinematic bifurcations and compliance of thick‐panel origami. A kinematic study is carried out to investigate the gripper's bifurcated motion modes. The hinge compliance is also taken into account to enhance the gripper's motion dexterity. Theoretical analysis and experiments are conducted to demonstrate both features, thereby paving the foundation for achieving dexterous motions with a simplified control strategy. Aided by a differential mechanism, the gripper can effectively interact with objects with the actuation inputs from only two motors. Objects including balls, cuboids, and cones are explored for in‐hand manipulation under different motion modes, showing varied trajectories. With the integration of tactile sensors at the fingertips, we have also revealed the gripper's potential for classification tasks.

Modulation of Motor Cortical Inhibition and Facilitation by Touch Sensation from the Glabrous Skin of the Human Hand.

Touch sensation from the glabrous skin of the hand is essential for precisely controlling dexterous movements, yet the neural mechanisms by which tactile inputs influence motor circuits remain largely unexplored. By pairing air-puff tactile stimulation on the hand's glabrous skin with transcranial magnetic stimulation (TMS) over the primary motor cortex (M1), we examined the effects of tactile stimuli from single or multiple fingers on corticospinal excitability and M1's intracortical circuits. Our results showed that when we targeted the hand's first dorsal interosseous (FDI) muscle with TMS, homotopic (index finger) tactile stimulation, regardless of its point (fingertip or base), reduced corticospinal excitability. Conversely, heterotopic (ring finger) tactile stimulation had no such effect. Notably, stimulating all five fingers simultaneously led to a more pronounced decrease in corticospinal excitability than stimulating individual fingers. Furthermore, tactile stimulation significantly increased intracortical facilitation (ICF) and decreased long-interval intracortical inhibition (LICI) but did not affect short-interval intracortical inhibition (SICI). Considering the significant role of the primary somatosensory cortex (S1) in tactile processing, we also examined the effects of downregulating S1 excitability via continuous theta burst stimulation (cTBS) on tactile-motor interactions. Following cTBS, the inhibitory influence of tactile inputs on corticospinal excitability was diminished. Our findings highlight the spatial specificity of tactile inputs in influencing corticospinal excitability. Moreover, we suggest that tactile inputs distinctly modulate M1's excitatory and inhibitory pathways, with S1 being crucial in facilitating tactile-motor integration.

Multimodal Soft Robotic Actuation and Locomotion.

Diverse and adaptable modes of complex motion observed at different scales in living creatures are challenging to reproduce in robotic systems. Achieving dexterous movement in conventional robots can be difficult due to the many limitations of applying rigid materials. Robots based on soft materials are inherently deformable, compliant, adaptable, and adjustable, making soft robotics conducive to creating machines with complicated actuation and motion gaits. This review examines the mechanisms and modalities of actuation deformation in materials that respond to various stimuli. Then, strategies based on composite materials are considered to build toward actuators that combine multiple actuation modes for sophisticated movements. Examples across literature illustrate the development of soft actuators as free-moving, entirely soft-bodied robots with multiple locomotion gaits via careful manipulation of external stimuli. The review further highlights how the application of soft functional materials into robots with rigid components further enhances their locomotive abilities. Finally, taking advantage of the shape-morphing properties of soft materials, reconfigurable soft robots have shown the capacity for adaptive gaits that enable transition across environments with different locomotive modes for optimal efficiency. Overall, soft materials enable varied multimodal motion in actuators and robots, positioning soft robotics to make real-world applications for intricate and challenging tasks.

HCDR-based motion planning for mobile manipulators with the continuous trajectory task

Mobile manipulators have been widely used in modern industrial fields due to their advantages of large operating workspace and high motion dexterity. For the application, the path planning has been a core foundation for its motion control. However, as the environmental complexity and performance requirements increase, existing methods are limited by low execution efficiency, and lack of comprehensive consideration of motion performances. A motion planning technique is proposed for mobile manipulators with continuous trajectory task. In this technique, a hierarchical constraints dimension reduction (HCDR) strategy is presented based on the task decomposition and performance requirements analysis of each stage. HCDR strategy aims to improve the execution efficiency of the algorithm through local operations of performance constraints and the local simplification of the distance calculation at different stages of the task. Models of inverse kinematics and performance indexes are established to provide basis for constraint conditions, including distance models with different accuracy, manipulability index model and trajectory tracing error model. Two optimization strategies are presented to solve the motion planning problem considering the overall performance of the system. And simulation results show that the three-level strategy has the higher convergence efficiency than the bi-level strategy, as well as can guarantee the motion performance of the system.

Kinematic Analysis of Multi-Section Opposite Magnetic Catheter Robots With Solution Multiplicity

Magnetic catheter robots have great potential for application in minimally invasive surgical interventions that require submillimeter soft catheters to be inserted into the body. Compared to other medical continuum robots, the kinematic characteristics of the magnetic continuum robot are required to be improved, including operating dexterity. The opposite magnetic continuum robot (OMCR), which has oppositely-magnetized magnets on the robot, is capable of deforming in large and high-order curvatures and shows improved dexterity. However, unstable kinematic behaviors emerge owing to solution multiplicity and affect the actual operation. For example, snapping, which indicates the sudden jump from one state to another, induces danger for medical operations. In addition, the motion sequence of the external mobile magnet affects the final state of OMCR. Therefore, in this study, we first analyze the reason for these emerging behaviors by understanding the solution multiplicity of an OMCR. We then modified the OMCR kinematic model with instability analysis and additional constraints, to predict the critical point for snapping and avoid other unexpected behavior for path planning. Herein, our study aims to analyze the stability of the OMCR with relatively unstable configurations in their actuation space to ensure stable and dexterous motions for medical applications. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The motivation of this work is to analyze, predict, and avoid the unexpected behaviors of the medical magnetic catheter robots, and ensure stable and dexterous operation. Submillimeter magnetic catheter robots have received considerable attention in the past ten years owing to their small size and dexterous motion. They have great potential for minimally invasive surgical interventions that require the navigation of “tighter corners” inside the human body. However, there may exist multiple local solutions under an external field, especially when the robot deforms in high-order curvature for dexterous operation. This situation induces unexpected behaviors and danger for medical use, such as a sudden jump from one state to another. Herein, we analyze the solution evolution as the external field varies and predict the unexpected behaviors using a modified kinematic model with instability analysis. Preliminary experiments demonstrated the effectiveness of the modified model, which can predict unexpected behaviors, and evaluate and enhance the stability during path planning. This method can be implemented for the dexterous and stable operation of magnetic catheter robots, which is significant for medical applications.

Prediction of Dexterous Finger Forces with Forearm Rotation using Motoneuron Discharges.

Motor unit (MU) discharge information obtained via electromyogram (EMG) decomposition can be used to decode dexterous multi-finger movement intention for neural-machine interfaces (NMI). However, the variation of the motor unit action potential (MUAP) shape resulted from forearm rotation leads to the decreased performance of EMG decomposition, especially under the real-time condition and then the degradation of motion decoding accuracy. The object of this study was to develop a method to realize the accurate extraction of MU discharge information across forearm pronated/supinated positions in the real-time condition for dexterous multi-finger force prediction. The FastICA-based EMG decomposition technique was used and the proposed method obtained multiple separation vectors for each MU at different forearm positions in the initialization phase. Under the real-time condition, the MU discharge information was extracted adaptively using the separation vector extracted at the nearest forearm position. As comparison, the previous method that utilized a single constant separation vector to extract MU discharges across forearm positions and the conventional method that utilized the EMG amplitude information were also performed. The results showed that the proposed method obtained a significantly better performance compared with the other two methods, manifested in a larger coefficient of determination (R2) and a smaller root mean squared error (RMSE) between the predicted and recorded force. Our results demonstrated the feasibility and the effectiveness of the proposed method to extract MU discharge information during forearm rotation for dexterous force prediction under the real-time conditions. Further development of the proposed method could potentially promote the application of the EMG decomposition technique for continuous dexterous motion decoding in a realistic NMI application scenario.

Validations of various in-hand object manipulation strategies employing a novel tactile sensor developed for an under-actuated robot hand.

Prisma Hand II is an under-actuated prosthetic hand developed at the University of Naples, Federico II to study in-hand manipulations during grasping activities. 3 motors equipped on the robotic hand drive 19 joints using elastic tendons. The operations of the hand are achieved by combining tactile hand sensing with under-actuation capabilities. The hand has the potential to be employed in both industrial and prosthetic applications due to its dexterous motion capabilities. However, currently there are no commercially available tactile sensors with compatible dimensions suitable for the prosthetic hand. Hence, in this work, we develop a novel tactile sensor designed based on an opto-electronic technology for the Prisma Hand II. The optimised dimensions of the proposed sensor made it possible to be integrated with the fingertips of the prosthetic hand. The output voltage obtained from the novel tactile sensor is used to determine optimum grasping forces and torques during in-hand manipulation tasks employing Neural Networks (NNs). The grasping force values obtained using a Convolutional Neural Network (CNN) and an Artificial Neural Network (ANN) are compared based on Mean Square Error (MSE) values to find out a better training network for the tasks. The tactile sensing capabilities of the proposed novel sensing method are presented and compared in simulation studies and experimental validations using various hand manipulation tasks. The developed tactile sensor is found to be showcasing a better performance compared to previous version of the sensor used in the hand.

Muscle-inspired soft robots based on bilateral dielectric elastomer actuators

Muscle groups perform their functions in the human body via bilateral muscle actuation, which brings bionic inspiration to artificial robot design. Building soft robotic systems with artificial muscles and multiple control dimensions could be an effective means to develop highly controllable soft robots. Here, we report a bilateral actuator with a bilateral deformation function similar to that of a muscle group that can be used for soft robots. To construct this bilateral actuator, a low-cost VHB 4910 dielectric elastomer was selected as the artificial muscle, and polymer films manufactured with specific shapes served as the actuator frame. By end-to-end connecting these bilateral actuators, a gear-shaped 3D soft robot with diverse motion capabilities could be developed, benefiting from adjustable actuation combinations. Lying on the ground with all feet on the ground, a crawling soft robot with dexterous movement along multiple directions was realized. Moreover, the directional steering was instantaneous and efficient. With two feet standing on the ground, it also acted as a rolling soft robot that can achieve bidirectional rolling motion and climbing motion on a 2° slope. Finally, inspired by the orbicularis oris muscle in the mouth, a mouthlike soft robot that could bite and grab objects 5.3 times of its body weight was demonstrated. The bidirectional function of a single actuator and the various combination modes among multiple actuators together allow the soft robots to exhibit diverse functionalities and flexibility, which provides a very valuable reference for the design of highly controllable soft robots.

A Novel Extensible Continuum Robot with Growing Motion Capability Inspired by Plant Growth for Path-Following in Transoral Laryngeal Surgery.

This article presents a novel extensible continuum robot (ECR) with growing motion capability for improved flexible access in transoral laryngeal procedures. The robot uses an extensible continuum joint with a staggered V-shaped notched structure as the backbone, driven by the pushing and pulling of superelastic Nitinol rods. The notched structure is optimized to achieve a wide range of extension/contraction and bending motion for the continuum joint. The successive and uniform deflection of the notches provides the continuum joint with excellent constant curvature bending characteristics. The bidirectional rod-driven approach expands the robot's extension capabilities with both pushing and pulling operations, and the superelasticity of the driving rods preserves the robot's bending performance. The ECR significantly increases motion dexterity and reachability through its variable length, which facilitates collision-free access to deep lesions by following the anatomy. To further exploit the advantages of the ECR in path-following for flexible access, a growing motion approach inspired by the plant growth process has been proposed to minimize the path deviation error. Characterization experiments are conducted to verify the performances of the proposed ECR. The extension ratio achieves up to 225.92%, and the average distal positioning error and hysteresis error values are 2.87% and 0.51% within the ±120° bending range. Compared with the typical continuum robot with a fixed length, the path-following deviation of this robot is reduced by more than 58.30%, effectively reducing the risk of collision during access. Phantom experiments validate the feasibility of the proposed concept in flexible access procedures.

A Telescopic Tendon-Driven Needle Robot for Minimally Invasive Neurosurgery.

This paper presents the design, characterization, and testing of a steerable needle robot for minimally invasive neurosurgery. The robot consists of a rigid outer tube and two telescopic tendon-driven steerable tubes. Through the rotation, translation, and bending of individual tubes, this telescopic tendon-driven needle robot can perform dexterous motion and follow the path of the tip. We presented the design of the needle robot and its actuation system, modeling of the robotic kinematics, characterization of the robot motion, results of the open-loop kinematic control, and demonstration of the follow-the-leader motion. The position error of the robot tip is 0.92 mm, and follow-the-leader motion error is 1.1 mm. Due to its small footprint and unique motion ability, the robot has the potential to be manipulated inside human brain and used for minimally invasive neurosurgery.

Exploring the Complex Phenotypes of Impaired Finger Dexterity in Mild-to-moderate Stage Parkinson's Disease: A Time-Series Analysis.

Impaired dexterity is an early motor symptom in Parkinson's disease (PD) that significantly impacts the daily activity of patients; however, what constitutes complex dexterous movements remains controversial. To explore the characteristics of finger dexterity in mild-to-moderate stage PD. We quantitatively assessed finger dexterity in 48 mild-to-moderate stage PD patients and 49 age-matched controls using a simple alternating two-finger typing test for 15 seconds. Time-series analyses of various kinematic parameters with machine learning were compared between sides and groups. Both the more and less affected hands of patients with PD had significantly lower typing frequency and slower typing velocity than the non-dominant and the dominant hands of controls (p = 0.019, p = 0.016, p < 0.001, p < 0.001). The slope of the typing velocity decreased with time, indicating a sequence effect in the PD group. A typing duration of 6 seconds was determined sufficient to discriminate PD patients from controls. Typing error, repetition, and repetition rate were significantly higher in the more affected hands of patients with PD than in the non-dominant hand of controls (p < 0.001, p = 0.03, p < 0.001). The error rate was constant, whereas the repetition rate was steep during the initiation of typing. A predictive model of the more affected hand demonstrated an accuracy of 70% in differentiating PD patients from controls. Our study demonstrated complex components of impaired finger dexterity in mild-to-moderate stage PD, namely bradykinesia with sequence effects, error, and repetition at the initiation of movement, suggesting that multiple neural networks may be involved in dexterity deficits in PD.

Bioinspired Soft Wrist Based on Multicable Jamming With Hybrid Motion and Stiffness Control for Dexterous Manipulation

Dexterous manipulation is important for modern logistics automation. Industrial robots remain inferior to human labor in this area, especially in handling unknown objects in unstructured scenarios. It is observed that the human wrist contributes significantly to the dexterous manipulation capability by agilely changing the hand orientation to approach the target object and adjusting wrist stiffness to adapt to dynamic interaction. Inspired by the human wrist, we propose a novel soft wrist to achieve hybrid motion/stiffness control in a compact and lightweight structure. The dexterous motion and stiffness adjustment are simultaneously enabled by a novel multicable jamming mechanism, which is achieved by a precalibration of the relationship between stiffness with robot length and bending angle to adapt to both compliant and forceful tasks. Dedicated experiments were performed to validate its motion dexterity and variable stiffness property. A soft grasping system was developed to demonstrate the manipulation capability of the soft wrist by tasking it with automatic packaging, which is challenging for robots. Overall, the proposed soft wrist demonstrates a promising solution to enhance robotic manipulation capability to a human comparable level.

“RobOstrich” Manipulator: A Novel Mechanical Design and Control Based on the Anatomy and Behavior of an Ostrich Neck

Flexible manipulators have high degrees of freedom and deformability, enabling dexterous movements and allowing for unexpected contacts with the environment. Underactuated tendon-drive mechanisms are the most widely adopted because of their simplicity and effectiveness. However, they suffer from difficulty in modeling and in achieving dexterity and structural stability. In this paper, we focus on ostriches, which can dexterously and swiftly move their flexible necks. We carried out a detailed dissection of ostrich necks and identified a specific musculo-tendon-skeletal structure. Based on the findings related to the structure, we came up with a novel mechanical design and control method manifested as a “RobOstrich” manipulator. Our actual robot experiments confirm that it exhibits similar movement patterns as an ostrich neck. It is also flexible yet structurally stable, enabling dexterous reaching movements. This work also contributes to biology by providing constructive understanding of the functionality of the morphology of an ostrich neck.