Flexible Robot Research Articles

3D-printing of conductive inks based flexible tactile sensor for monitoring of temperature, strain and pressure

Flexible multimodal tactile sensors have been widely used in health monitoring devices, flexible smart robots, and human–machine interfaces in intelligent automobiles. In the present work, conductive inks embedded with carbon fillers were optimized to fabricate flexible multimodal tactile sensors by a direct ink writing process. Results showed that rheological properties and printing speed were key factors to print conductive paths with controllable shape and good conductivity. Flexible multimodal tactile sensors were fabricated at different printing speeds, and the effects of printing speed on sensing characteristics were observed. The flexible multimodal tactile sensors printed with conductive inks exhibited excellent sensitivities for temperature (up to 0.172 °C−1), strain (1918.4), and pressure (610.208 kPa−1). Furthermore, cyclic loading–unloading tests revealed that the as-fabricated flexible multimodal tactile sensors were reliable and durable. Finally, the application potential of these sensors for multimodal perception was verified by detecting their responses to finger flexion and extension, finger pressing, and hot air flow. The as-designed flexible multimodal tactile sensors manifested excellent potentialities in health monitoring devices, flexible smart robots, and human–machine interfaces in intelligent automobiles.

An Origami-Inspired Negative Pressure Folding Actuator Coupling Hardness with Softness

Soft actuators have a high potential for the creative design of flexible robots and safe human–robot interaction. So far, significant progress has been made in soft actuators’ flexibility, deformation amplitude, and variable stiffness. However, there are still deficiencies in output force and force retention. This paper presents a new negative pressure-driven folding flexible actuator inspired by origami. First, we establish a theoretical model to predict such an actuator’s output force and displacement under given pressures. Next, five actuators are fabricated using three different materials and evaluated on a test platform. The test results reveal that one actuator generates a maximum pull force of 1125.9 N and the maximum push force of 818.2 N, and another outputs a full force reaching 600 times its weight. Finally, demonstrative experiments are conducted extensively, including stretching, contracting, clamping, single-arm power assistance, and underwater movement. They show our actuators’ performance and feature coupling hardness with softness, e.g., large force output, strong force retention, two-way working, and even muscle-like explosive strength gaining. The existing soft actuators desire these valuable properties.

Robotic Manipulation System Design and Control for Non-Contact Remote Diagnosis in Otolaryngology: Digital Twin Approach

Since the COVID-19 pandemic, the development of a non-contact medical robot that prevents infection is increasingly required due to the medical field’s heavy workload and emotional stress. To reduce workload and prevent infection, we propose a non-contact robotic diagnostic system that can be applied to conventional otolaryngology clinics. A digital twin model was used to leverage the initial design optimisation of the diagnostic robotic system. The proposed system was developed based on a master-slave robot architecture. The slave robot comprises a flexible endoscope manipulation robot and a parallel robot arm that controls other medical instruments. In contrast to the conventional approach that employs two hands, our flexible endoscope manipulation robot employs a novel 4 degrees of freedom (DOF) control mechanism to deal with an endoscope with a single robotic arm. Phantom experiments on the flexible endoscope system were performed to confirm the effectiveness of the proposed system. The experimental results demonstrate the usability of the proposed system in terms of three evaluation metrics (i.e. diagnosis completion time, NASA task load index (NASA-TLX), and subjective risk score).

A liquid-free conducting ionoelastomer for 3D printable multifunctional self-healing electronic skin with tactile sensing capabilities.

Conductive elastomers with both softness and conductivity are widely used in the field of flexible electronics. Nonetheless, conductive elastomers typically exhibit prominent problems such as solvent volatilization and leakage, and poor mechanical and conductive properties, which limit their applications in electronic skin (e-skin). In this work, a liquid-free conductive ionogel (LFCIg) with excellent performance was fabricated by utilizing the innovative double network design approach based on a deep eutectic solvent (DES). The double-network LFCIg is cross-linked by dynamic non-covalent bonds, which exhibit excellent mechanical properties (2100% strain while sustaining a fracture strength of 1.23 MPa) and >90% self-healing efficiency, and a superb electrical conductivity of 23.3 mS m-1 and 3D printability. Moreover, the conductive elastomer based on LFCIg has been developed into a stretchable strain sensor that achieves accurate response recognition, classification, and identification of different robot gestures. More impressively, an e-skin with tactile sensing functions is produced by in situ 3D printing of sensor arrays on flexible electrodes to detect light weight objects and recognize the resulting spatial pressure variations. Collectively, the results demonstrate that the designed LFCIg has unparalleled advantages and presents wide application potential in flexible robotics, e-skin and physiological signal monitoring.

Research on a New Rehabilitation Robot for Balance Disorders.

The treatment of patients with balance disorders is an urgent problem to be solved by the medical community. The causes of balance disorders are diverse. An aging population, traffic accidents, stroke, genetic diseases and so on are all possible factors. It has brought great pain and inconvenience to patients and their families. At present, there are two main types of assisted rehabilitation training robots for patients with balance disorders: exoskeleton robots and end robots. The exoskeleton robot is generally installed on the outside of the patient's body to follow their movement, which can support the weight of the body and provide power support to help the patient train and recover lower limb ability. The use of end robots is usually to secure the patient's foot to the motion platform and control the pedal to drive the lower limbs to conduct gait training. Such passive training is more suitable for patients with severe disorders. The patient has low awareness of active participation. This paper focuses on research on end rehabilitation training robots for balance disorders. In this paper, a robotic system for rehabilitation training of patients with balance disorders is invented. The robot body is a 9 degree of freedom (DOF) redundant series-parallel hybrid motion platform. Two sets of motion platforms with symmetrical mirror images are used together to simulate different motion modes of the human body and drive the human body to move. Each set of motion platforms is composed of a 6-DOF vestibular parallel device and a 3-DOF proprioception parallel device. It has the advantages of DOF decoupling and fast response, proposing a new structural form for the design of proprioceptive and vestibular simulation platforms. The robot's functional level can be divided into a vestibular sense module and a proprioception module according to the structure. The two modules can work independently to achieve different functions or work together to achieve complex motion and multisensory fusion. This robot is a redundant mechanism device with 9 DOFs. Through a reasonable distribution of DOF and motion, the robot's working space can be increased, and the robot's flexibility and motion performance can be improved. In this paper, a trajectory tracking control algorithm for vestibular and proprioceptive simulation is proposed, which can provide unlimited body sense training for patients within the robot's limited motion range.

An aquatic biomimetic butterfly soft robot driven by deformable photo-responsive hydrogel.

Taking inspiration from the locomotor behaviors of a butterfly, we have developed an underwater soft robot that imitates its movements. This biomimetic robot is constructed using a deformable photo-responsive material that exhibits high biological compatibility and impressive deformation capabilities in response to external stimuli. First, we investigate composite materials consisting of poly-N-isopropylacrylamide (PNIPAM) and multi-walled carbon nanotubes (MWCNTs). Then, using photocuring printing technology, we successfully fabricate a biomimetic butterfly soft robot utilizing these composite materials. The robot is driven by visible light, enabling it to achieve periodic wing movement and fly upward at an average speed of 3.63 mm s-1. In addition, the robot achieves additional functionalities such as flying over obstacles and carrying small objects during the ascending flight. These outcomes have a significant impact on the advancement of flexible biomimetic robots and offer valuable insights for the research of biomimetic robots driven by visible light.

An RNN-LSTM Enhanced Compact and Affordable Micro Force Sensing System for Interventional Continuum Robots With Interchangeable End-Effector Instruments

Micro force sensing in various clinical scenarios is a challenging issue to be addressed. It is highly difficult to trade off the size, cost, and measurement accuracy of a micro force sensing system. In this paper, a compact and affordable micro force sensing system enhanced by deep neural network is proposed. A three-axis force sensor is designed and fabricated with a footprint of only 14 mm and is employed to transform the force on the material structure into more accurate distance information. Such a sensor configuration can be seamlessly interfaced with the distal end of our in-house compliant and flexible continuum robot. On top of that, the RNN-LSTM network is exploited to augment the micro force sensing capability of the distal end-effector of the robot, which addresses the limitation on the nonlinear force issue of the continuum robot and the material itself. The RNN-LSTM network alone can be employed to perform force curve fitting for specific interventional tasks. The results indicate that more than 90% accuracy has been achieved, and the network can be applied to large-scale continuum robot-assisted interventional scenario deployment and teleoperation force perception.

A Flexible Magnetic Soft Continuum Robot for Manipulation and Measurement at Microscale

Magnetic soft continuum robots have received interest in diverse fields, because of their active steering and remote control capabilities. However, a more challenging task is the development of magnetic soft continuum robots for analyzing the mechanical properties of biological tissue during intravascular treatments. Here, we present a force-controlled soft continuum robot with a magnetic end-effector for measurement of biological mechanical properties. The magnetically driven system contains a set of Helmholtz coils and a permanent magnet. The Helmholtz coils produce an oscillating magnetic field for overcoming friction. The permanent magnet is responsible for steering and providing traction for forward motion. The force on the magnetic tip was calibrated with a soft rod with a known elasticity coefficient. Experimental results indicated that the magnetic soft continuum robot successfully achieved manipulation and stiffness measurement of biological embryos. This strategy for mechanical property analysis of biological tissue expands the opportunities for use of soft continuum robots and broadens the field of functionalization for continuum microrobots.

Worm blobs as entangled living polymers: from topological active matter to flexible soft robot collectives.

Recently, the study of long, slender living worms has gained attention due to their unique ability to form highly entangled physical structures, exhibiting emergent behaviors. These organisms can assemble into an active three-dimensional soft entity referred to as the "blob", which exhibits both solid-like and liquid-like properties. This blob can respond to external stimuli such as light, to move or change shape. In this perspective article, we acknowledge the extensive and rich history of polymer physics, while illustrating how these living worms provide a fascinating experimental platform for investigating the physics of active, polymer-like entities. The combination of activity, long aspect ratio, and entanglement in these worms gives rise to a diverse range of emergent behaviors. By understanding the intricate dynamics of the worm blob, we could potentially stimulate further research into the behavior of entangled active polymers, and guide the advancement of synthetic topological active matter and bioinspired tangling soft robot collectives.

On Tracking Control of Robot Manipulator with Flexible Joints in Operational Space

In this paper, an adaptive control framework and a command-filtered control framework are proposed for flexible joint robot manipulators to track a desired trajectory in the workspace. First, we present an adaptive control algorithm which ensures that the output (the end-effector) of the uncertain manipulator with flexible joints tracks a desired trajectory in the operational space. Subsequently, a control algorithm is synthesized with the command-filtered technique to eliminate the requirements of the joint-jerk feedback and the third-order derivative of system models. The advantages of the proposed control frameworks are guaranteeing the tracking performance in the workspace and scaling down the complexity of the controller. Therefore, the proposed approaches can be applied to heterogeneous robotic systems and are easier to implement. The stability and convergence of the closed-loop systems are analyzed based on Lyapunov technique. Simulation results are provided to show the efficiency of the proposed control frameworks.

High Grasp Ability Artificial Muscle Flexible Robot Design and Verification

High Grasp Ability Artificial Muscle Flexible Robot Design and Verification

Magnetically controlled flexible micro-robots based on magnetic particle arrangement

This paper reports a simplified method for preparing magnetically controlled flexible robots with swimming, transport, and grasping functions.

Control of Double Link Flexible Robotic Manipulator System

Flexible manipulator is widely used in the implementation of industial robotic due to its advantages such as low weight, low power consumption, higher load capacity, high-speed operation, small actuators and low production costs. However, the position and speed of flexible manipulator system are very difficult to control due to the tip vibration that result in degradation of performance. Modelling and control of a double-link flexible robot manipulator are presented in this study. Controlling the movement of a double-link manipulator, on the other hand, has proven to be a challenging task, especially when a flexible framework is used. Moreover, most double-link flexible manipulator system models are not developed based on real hardware. Hence, this project aims to develop a Solidworks design for double link flexible robotics manipulator (DLFRM) as well as a real hardware prototype. The control position performance of DLFRM was analyzed, and the controllers were tested on a hardware prototype. This project started with a simulation of both controllers, which are PID and FLC. The simulation was designed in Solidworks and exported to Simulink and then converted as Simscape. Then, the hardware for each controller was validated using the control parameter in the simulation. The joints for the robot manipulator were designed in Solidwork and built using 3D printing.

Magneto-Thermomechanically Reprogrammable Mechanical Metamaterials.

Future active metamaterials for reconfigurable structural applications require fast, untethered, reversible, and reprogrammable (multimodal) transformability with shape locking. Magnetic control has a superior advantage for fast and remotely controlled deployment; however, a significant drawback is needed to maintain the magnetic force to hold the transformation, limiting its use in structural applications. The shape-locking property of shape-memory polymers (SMPs) can resolve this issue. However, the intrinsic irreversibility of SMPs may limit their reconfigurability as active metamaterials. Moreover, to date, reprogrammable methods have required high power with laser and arc welding proving to be energy-inefficient control methods. In this work, a magneto-thermomechanical tool is constructed and demonstrated, which enables a single material system to transform with untethered, reversible, low-powered reprogrammable deformations, and shape locking via the application of magneto-thermomechanically triggered prestress on the SMP and structural instability with asymmetric magnetic torque. The mutual assistance of two physics concepts-magnetic control combined with the thermomechanical behavior of SMPsis demonstrated, without requiring new materials synthesis and high-power energy for reprogramming. This approach can open a new path of active metamaterials, flexible yet stiff soft robots, multimodal morphing structures, and mechanical computing devices where it can be designed in reversible and reprogrammable ways.

Physics-informed sparse identification of bistable structures

The design of bistable structures is a hot topic in the last decade due to its wide application in smart actuators, energy harvesters, flexible robotics, etc. The characterization of the nonlinear restoring force of bistable structures plays a significant role in modeling and enhancing dynamic performance. However, the traditional nonparametric identification methods may have insufficient accuracy or even be invalid because of numerical differentiation procedures and static fitting. Besides, the modern data-driven sparse regression identification methods rely highly on the assumed nonlinear basis functions and lack interpretability. In this paper, a physics-informed sparse identification method is proposed for the nonlinear restoring force identification of bistable structures. The function of the nonlinear restoring force is physically informed by the derived equation of the Hilbert transform and parameter fitting. Furthermore, sparse identification is conducted based on the free vibration responses of the bistable vibrator. The numerical studies verify the effectiveness of the proposed algorithm under the noise level of 30 dB. Experimental measurement is conducted on a magnetic coupled bistable beam to perform the model identification. It has been demonstrated that the reconstructed dynamic response and nonlinear restoring force both keep in good agreement with the measured ones.

Research on the Dynamic Behaviors in the Sliding Friction of Silicone

With the promotion of soft viscoelastic materials in the field of flexible bionic robots, the behavior of sliding friction between soft viscoelastic materials and rigid materials such as metals has attracted great attention. In this study, the research object was silicone, and a research method combining a dynamic force testing technique and a non-contact optical testing technique for deformation and strain was proposed to study the frictional behavior of silicone and the effect of the tooth structure surface on the sliding friction. We analyzed the temporal changes in the friction force for different loads, the dynamic characteristics of large deformation and micro-strain on the front side (define the contact surface as the bottom surface) of the silicone. The results showed that within a certain range, the sliding friction coefficient of the silicone increased monotonically with increasing load, and there were stick-slip and deformation waves during the relative motion. The larger the load was, the faster the deformation wave propagated, and the tooth structure surface had sliding friction anisotropy.

Practically Robust Fixed-Time Convergent Sliding Mode Control for Underactuated Aerial Flexible JointRobots Manipulators

The control of an aerial flexible joint robot (FJR) manipulator system with underactuation is a difficult task due to unavoidable factors, including, coupling, underactuation, nonlinearities, unmodeled uncertainties, and unpredictable external disturbances. To mitigate those issues, a new robust fixed-time sliding mode control (FxTSMC) is proposed by using a fixed-time sliding mode observer (FxTSMO) for the trajectory tracking problem of the FJR attached to the drones system. First, the underactuated FJR is comprehensively modeled and converted to a canonical model by employing two state transformations for ease of the control design. Then, based on the availability of the measured states, a cascaded FxTSMO (CFxTSMO) is constructed to estimate the unmeasurable variables and lumped disturbances simultaneously in fixed-time, and to effectively reduce the estimation noise. Finally, the FxTSMC scheme for a high-order underactuated FJR system is designed to guarantee that the system tracking error approaches to zero within a fixed-time that is independent of the initial conditions. The fixed-time stability of the closed-loop system of the FJR dynamics is mathematically proven by the Lyapunov theorem. Simulation investigations and hardware tests are performed to demonstrate the efficiency of the proposed controller scheme. Furthermore, the control technique developed in this research could be implemented to the various underactuated mechanical systems (UMSs), like drones, in a promising way.

A programable biomimetic actuator with large and reversible deformation based on commercial poly (ethylene-co-vinyl acetate)

Due to the reversible and remote actuation under applied voltage, shape-memory polymer (SMP) based on semi-crystalline polymer are explored for developing soft actuators, where the commercial material, poly (ethylene-co-vinyl acetate) (EVA), has great potential for the large-scale application to construct an actuator, due to its cost-effective and crystal-adjustable merits. However, the small deformation of SMP based on commercial poly (ethylene-co-vinyl acetate) (EVA) (usually less than 10%) is always a problem which limits their practical application. Herein, combining the pre-stretched and photo-crosslinked EVA, a biomimetic actuator with large reversible deformation (∼20%) is designed and fabricated by compounding with polyimide (PI) with screen-printed Ag conductive network. Using chemical crosslinking points as the new skeleton domain can allow the original crystal of the skeleton domain to involve in the reversible actuation to obtain large deformation. Meanwhile, due to the chemical crosslinking points formed by photo-crosslinking in EVA, the resultant composites can be actuated at temperatures above the melting point, which is critical to reducing the constraints of actuating conditions. In addition, the perfect conductivity prepared by the Ag conductive network endows this composite with a low voltage (≤25 V/m) actuating capacity. Based on the good programming capability of composites, various modes containing zero-set reversible actuation are designed. Particularly, a quadruped robot can stand up quickly under an applied voltage of 5 V and return to a zero-set state after voltage removal, which proves the application potential of the composite in flexible robotics.

Annelid-inspired high-elongation origami robot using partial material removal

Existing soft robots face challenges given the need for an improved flexible robot elongation rate, bending angle and movement flexibility in space target acquisition, disaster search and rescue, unknown environment detection and other fields. Yoshimura tubular origami shows good applied performance with regard to the axial elongation ratio. However, due to the characteristics of nonrigid folding and a negative Poisson’s ratio, the axial elongation length and bending angle of the Yoshimura tubular origami mechanism are limited. Annelids show highly flexible body movement. By analyzing the main factors limiting the axial elongation rate of the Yoshimura tubular origami mechanism and imitating the morphological characteristics and motion mechanism of annelid somite joints, we proposed a method to achieve high flexibility and large angle bending of a tubular origami mechanism based on local material removal and macroscopic elimination of the negative Poisson’s ratio. Combined with a Ni–Ti memory alloy wire segmented driving scheme based on force constraints and geometric constraints a continuous origami robot is designed. The optimal cutting amount of the origami mechanism is determined by experiments, and the maximum elongation ratio and bending angle of the origami mechanism reach 2.5 and 3 times those before material removal, respectively. The paper folding module unit was solved in a kinematic analysis workspace. Finally, a prototype was used to verify the performance and demonstrate the application potential of the robot in an unstructured rescue scene.

Control of Flexible Manipulator Robots Based on Dynamic Confined Space of Velocities: Dynamic Programming Approach

Linear Parameter Varying models-based Model Predictive Control (LPV-MPC) has stood out in manipulator robots because it presents well-rejection to dynamic uncertainties in flexible joints. However, it has become too weak when the MPC's optimization problem does not include kinematic constraints-based conditions. This paper uses dynamic confined space of velocities (DCSV) to include these conditions as a recursive polytopic constraint, guaranteeing optimal dependency on a simplex scheduling parameter. To this end, the local frame's velocities and torque/force preload of joints (related to violation of kinematic constraints) are associated with different time scale dynamics such that DCSV correlates them as a polytope. So, a classical LPV-MPC will be updated using a dynamic programming approach according to the DCSV-based polytope. As a result, one lemma about DCSV-based recursive polytope and a five-step procedure for two decoupled close-loop schemes with different time scales compose the LPV-MPC proposed method. Numerical validation shows that even for relevant flexibility situations, trajectory tracking performance is improved by tuning finite horizons and optimization problem constraints regarding DCSV's behavior.