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Concentric push–pull robots delivered through flexible endoscopes work best if their laser-cut transmission tubes have high axial stiffness, high torsional stiffness and low bending stiffness. This paper simultaneously addresses all three output stiffness values in the transmission design problem, explicitly considering axial stiffness, whereas prior work on laser-cut tube design has focused on the bending/torsional stiffness ratio. We demonstrate an inherent trade-off present in existing laser-cut patterns: it is difficult to simultaneously achieve high axial stiffness and low bending stiffness because these properties are very tightly correlated. To break this correlation and design all three stiffness independently, we propose a new type of laser material removal pattern that leverages local stiffness asymmetry (EI$x_{}$$\ne$ EI$y_{}$) in discrete bending segments separated by segments of solid tube. These discrete asymmetric segments are then rifled down the tube to achieve global stiffness symmetry. We parameterize the design and provide a study of the properties through finite-element analysis. We also consider the effect of interference between the tubes when the discrete segments are not aligned. Results show that our discrete asymmetric segment concept can achieve high axial stiffness and torsional stiffness better than previously suggested laser patterns while maintaining equally low bending stiffness. We also experimentally validated the proposed design’s properties and actuation performance with professionally manufactured prototype Nitinol tubes for use in an endoscopic robot system.

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In this paper, we present an efficient finite element framework for modeling the finite deformations of slender magneto-active elastomers (MAE) under applied magnetic fields or currents. For the convenience of numerical modeling, magnetic field is defined at fixed spatial coordinates in the background space rather than in the elastic MAEs using material coordinates. The magnetic field will vary with free or localized currents while the spatial distribution of the magnetic field will evolve with the motion or deformation of the MAE materials, which is actuated by the surface or body forces induced by external magnetic fields or equivalent currents. A staggered strategy and a Riks method are introduced to solve the strongly coupled governing equations of the magnetic field and displacement field using finite element method. The mesh distortion along the interfaces between MAE domain and free-space domain is resolved by considering concurrent deformation of the mesh in these two domains. A few 2D numerical examples demonstrate the validity and efficiency of the developed model for simulating large deformation of MAE with non-uniform spatial magnetic field under different actuation sources such as free currents, magnetization or external magnetic field. This framework offers a new solution strategy for modeling mechano-magneto problems of MAEs and will help rational design and analysis of MAE-based actuators and soft robotics in the future.

We study long-term electrical resistance dynamics in mycelium and fruit bodies of oyster fungi P. ostreatus. A nearly homogeneous sheet of mycelium on the surface of a growth substrate exhibits trains of resistance spikes. The average width of spikes is c. 23min and the average amplitude is c. 1k$\mathrm{\Omega }$. The distance between neighboring spikes in a train of spikes is c. 30min. Typically, there are 4–6 spikes in a train of spikes. Two types of electrical resistance spikes trains are found in fruit bodies: low frequency and high amplitude (28min spike width, 1.6k$\mathrm{\Omega }$ amplitude, 57min distance between spikes) and high frequency and low amplitude (10min width, 0.6k$\mathrm{\Omega }$ amplitude, 44min distance between spikes). The findings could be applied in monitoring of physiological states of fungi and future development of living electronic devices and sensors.

This paper presents a method for determining material constants of hyperelastic material used for building the soft robotic actuators. Sixty testpieces were made of silicone rubber with a shore A hardness from 20 A to 45 A. Each of them was then subjected to the uniaxial tensile test to obtain the stress–strain relationship, which is a key factor to evaluate the compatibility of the common six forms of strain energy density function for hyperelastic material. The sum of square error was used to determine the most relevant constitutive models, which are Ogden third order, Polynomial second order, and Yeoh, as well as parameter values of the corresponding materials. To analyze the appropriateness of these models for computation, six pneumatic soft actuators were built from materials with different hardness and tested for various pressures. From the simulation and experimental results, the model Yeoh has yielded the highest accuracy. This outcome forms a firm basis for the determination of suitable material in the computation and simulation of the pneumatic soft actuator. Besides, the obtained experimental results in this paper could be included in the database of hyperelastic material with different hardness for further simulation in the related field.

This paper proposes a compliant motion control for human-cooperative robots to absorb collision force when persons accidentally touch the robots even while the robot is manipulating an object. In the proposed method, an external force estimator, which can distinguish the net external force from the object manipulation force, is realized using an inverse dynamics model acquired by a recurrent neural network (RNN). By implementing a mechanical impedance control to the estimated external force, the robot can quickly and precisely carry the object keeping the mechanical impedance control functioned and can generate a compliant motion to the net external force only when the person touches it during manipulation. Since the proposed method estimates the external force from the generalized force based on the learned inverse dynamics, it is not necessary to install any sensors on the manipulated object to measure the external force. This allows the robot to detect the collision even when the person touches anywhere on the manipulated object. The RNN inverse dynamics model is evaluated by the leave-one-out cross-validation and it was found that it works well for unknown trajectories excluded from the learning process. Although the details were omitted due to the limitation of the page length, similar to the simulations, the RNN inverse dynamics model was evaluated using unknown trajectories in the six degree-of-freedom experiments, and it has been verified that it functions properly even for the unknown trajectories. Finally, the validity of the proposed method has been confirmed by experiments in which a person touches a robot while it is manipulating an object with six degrees of freedom.

Continuum manipulators enable minimally-invasive surgery on the beating heart, but the challenges involved in manually controlling the manipulator’s tip position and contact force with the tissue result in failed procedures and complications. The objective of this work is to achieve autonomous robotic control of a continuum manipulator’s position and force in a beating heart model. We present a model-less hybrid control approach that regulates the tip position/force of manipulators with unknown kinematics/mechanics, under unknown constraints along the manipulator’s body. The algorithms estimate the Jacobian in the presence of heartbeat disturbances and sensor noise in real time, enabling closed-loop control. Using this model-less control approach, a robotic catheter autonomously traced clinically relevant paths on a simulated beating heart environment while regulating contact force. A gating procedure is used to tighten the treatment margins and improve precision. Experimental results demonstrate the capabilities of the robot ($1.4\pm 1.1$mm–$1.9\pm 1.4$mm tracking error) while user demonstrations show the difficulty of manually performing the same task ($2.6\pm 2.0$mm–$4.3\pm 3.9$mm tracking error). This new, robotically-enabled contiguous ablation method could reduce ablation path discontinuities, improve consistency of treatment, and therefore improve clinical outcomes.

Soft robotics are robotic systems made of materials that are similar in softness to human soft tissues. Recent medical soft robot designs, including rehabilitation, surgical, and diagnostic soft robots, are categorized by application and reviewed for functionality. Each design is analyzed for engineering characteristics and clinical significance. Current technical challenges in soft robotics fabrication, sensor integration, and control are discussed. Future directions including portable and robust actuation power sources, clinical adoptability, and clinical regulatory issues are summarized.

With the increased demand for endoscopic diagnosis in the upper gastrointestinal (GI) tract, gastric simulators have been developed for endoscopy training. However, most of them remain nonideal due to their static and nondistensible nature. This paper presents a new soft robotic gastric simulator, comprising mainly of a silicone-based stomach model that mimics the size and inner surface condition of a human stomach. It also features peristaltic effect on its stomach wall via five cable loop-driven mechanisms, sphincter mechanisms at two ends of the stomach model, and structural pathology phantoms that can be magnetically controlled for multi-location deployment. Finite element simulation of the stomach behavior was performed under different insufflation pressures to determine the cable loop mechanism design parameters. During the simulator evaluation, the performances of the sphincters and cable loop mechanisms were first characterized. The simulator was then actuated to provide sequential contraction across the stomach model at different contraction ratios, leading to intragastric pressures similar to those reported in the literature. Finally, a preliminary user study was performed to face validate the simulator in terms of its realism, usability, and usefulness for endoscopy training. It is envisioned that the soft robotic gastric simulator could be adopted in endoscopy training programs to replace the use of animal models.

Soft actuators are a new generation of robotic actuators designed for safer and more adaptable physical human-robot interaction, that can be triggered by various stimulating mechanisms, including pneumatic, electric, electromagnetic, light, magnetic, and thermal sources. Among the different types of soft actuators, thermoresponsive ones that utilize heat as the stimulus show great potential due to their ability to deliver a relatively high force-to-size ratio without the need for external air pumps, tethers, high voltage sources, or complex designs. However, a major drawback of such actuators is their limited bandwidth. Traditional methods rely on Joule heating for actuation, with the actuator deflating when the heat source is turned off and ambient temperature takes over. Recently, the Peltier mechanism has been introduced as an alternative approach for active heating and cooling. This research paper presents a comparative analysis of the Peltier and flexible heater mechanisms in terms of the bandwidth and energy consumption of phase-change thermo-active soft actuators. The study aims to assess the potential of Peltier-based actuation in addressing the bandwidth limitations observed in traditional soft actuators. The findings reveal that Peltier-based actuation can significantly improve actuation speed in thermoresponsive soft actuators. However, it is important to note that the performance of Peltier-based actuators decreases after a few cycles unless additional measures, such as the use of an external fan, are implemented. This increase in performance comes at the cost of higher energy consumption, which should be carefully considered in practical applications.

Soft robotics provides a new and exciting approach to design robots. Often inspired by the remarkable performances of biological systems a number of soft robotic designs have been proposed and implemented. Despite their great potential with respect to safety, energy efficiency, and adaptivity, soft robotics still faces a number of fundamental problems, e.g. their inherent complex dynamics that makes it difficult to apply classical control approaches. Morphological computation, a concept that understands that physical bodies can carry out computation, has the great potential to overcome this challenge by providing a novel point of view. Recent theoretical models on morphological computation as well real-world proof of concepts suggest that these unwanted complex dynamics of soft bodies can be actually beneficial and that they can be exploited as a computational resource. As a result, morphological computation allows to simplify the control and learning tasks by outsourcing computation to the physical body and, therefore, pointing to a potential solution for the control problem in soft robotics.

This paper is presented for the Special Session “Workshop on Soft Robotic Systems — Locomotion, posture and motion control”.

The purpose of this work is to present a novel control approach for a tendon driven soft robotic system using a Fractional Order (FO) controller. As the complex system is difficult to model, an advanced robust controller is applied based on a simplified model. The FO controller is used to meet the control specifications, taking advantage of the introduction of its fractional order α. Simulation and experimental data are presented to validate the approach.