The images captured by vision-based tactile sensors carry information about high-resolution tactile fields, such as the distribution of the contact forces applied to their soft sensing surface. However, extracting the information encoded in the images is challenging and often addressed with learning-based approaches, which generally require a large amount of training data. This article proposes a strategy to generate tactile images in simulation for a vision-based tactile sensor based on an internal camera that tracks the motion of spherical particles within a soft material. The deformation of the material is simulated in a finite element environment under a diverse set of contact conditions, and spherical particles are projected to a simulated image. Features extracted from the images are mapped to the three-dimensional contact force distribution, with the ground truth also obtained using finite-element simulations, with an artificial neural network that is therefore entirely trained on synthetic data avoiding the need for real-world data collection. The resulting model exhibits high accuracy when evaluated on real-world tactile images, is transferable across multiple tactile sensors without further training, and is suitable for efficient real-time inference.

Numerous recent advances in robotics have been inspired by the biological principle of tensile integrity-or "tensegrity"-to achieve remarkable feats of dexterity and resilience. Tensegrity robots contain compliant networks of rigid struts and soft cables, allowing them to change their shape by adjusting their internal tension. Local rigidity along the struts provides support to carry electronics and scientific payloads, while global compliance enabled by the flexible interconnections of struts and cables allows a tensegrity to distribute impacts and prevent damage. Numerous techniques have been proposed for designing and simulating tensegrity robots, giving rise to a wide range of locomotion modes, including rolling, vibrating, hopping, and crawling. In this study, we review progress in the burgeoning field of tensegrity robotics, highlighting several emerging challenges, including automated design, state sensing, and kinodynamic motion planning.

Soft actuators have received extensive attention in the fields of soft robotics, biomedicine, and intelligence systems owing to their advantages of pliancy, silence, and essential safety. However, most existing soft actuators have only single actuation elements and lack sensing. Therefore, it is difficult for them to perform complex motions with multiple degrees of freedom (multi-DOFs) and high precision. This article reports a miniature columnar dielectric elastomer actuator (DEA) with multi-DOF actuation and sensing, which was fabricated with an electroactive polymer acrylic film (Very High Bond [VHB] acrylic film by 3M Company) and carbon black grease electrodes. The arrangement of the simulation electrodes on the VHB was optimized to realize multi-DOF actuation, and the sensing electrodes were configured on the outer part of the DEA to realize real-time sensing. The results showed that the soft actuator can achieve all-round actuation through the selective power of the stimulation electrodes with a controllable voltage. The maximum bending angle and axial strain of the actuator reached 50° and 13%, respectively. Moreover, the deformation modes, direction, and quantity could be precisely measured using the integrative sensing function. In addition, to demonstrate the advantages of the proposed actuator, a manipulator with multiple actuators was designed and controlled to realize different actions of screwing and grasping with sensing. This research is useful not only for the design of multifunctional soft actuators but also for the development of soft robots with flexible, complex, and precisely controllable motions.

<div>Compared to most conventional industrial end effectors, electroadhesive</div><div>grippers enable the handling of sensitive, soft, or air-permeable materials [1]. This</div><div>makes them highly suitable for integration into soft robotic designs. The prehension</div><div>force is based on a strong electric field generated by electrodes resulting in a</div><div>polarisation of the dielectric and the generation of mirror charges in the workpiece.</div><div>When the electrode supply voltage is deactivated, the electric field rapidly drops, but an</div><div>electrostatic field remains due to the remanent polarisation of the dielectric. The</div><div>residual charge on the gripper surface reduces only slowly and, in combination with</div><div>other influencing factors, can prevent the workpiece from being ejected temporarily or</div><div>completely. A solution to this problem is presented by means of a magnetically</div><div>deformable soft gripper surface based on a combination of gripper dielectric and a</div><div>magneto-active polymer (MAP) actuator. The increased distance between the</div><div>workpiece and the dielectric enables precise and controlled workpiece ejection.<br><br><div>In addition to compliance and deformability, the employment of soft smart materials</div><div>enables the integration of self-sensing mechanisms for the measurement of surface</div><div>deformation. Direct mechanical coupling between the magnetic polymer and the</div><div>electrodes allows the actual deformation of the surface to be determined. The ability to</div><div>measure this deformation allows the magnetic field to be increased until the required</div><div>displacement is reached, regardless of the prevailing adhesion forces. Since</div><div>electroadhesive forces are also dependent on the workpiece materials, simply applying</div><div>a fixed magnetic flux would not be sufficient to achieve the same deformation for</div><div>every material. The self-sensing capability is independent of the gripping process and</div><div>can therefore also be used to recognise a particular surface topology. By applying a</div><div>mechanical force, the end effector can be pressed onto a three-dimensional workpiece,</div><div>causing the surface to deform inwards and physically comply with the workpiece</div><div>shape. The deformation achieved can then be targeted by the magnetic drive before</div><div>each gripping process, thereby creating optimum contact with the workpiece. Ejection</div><div>of the workpiece then follows by means of an inverse process, whereby the</div><div>deformation of the surface is reversed and the workpiece ejected by reducing the</div><div>contact area.<br><br><div>Embedded electrically conductive thermoplastic electrodes within the soft silicone</div><div>dielectric have the necessary flexibility to support such movements whilst serving as</div><div>the necessary electrodes for electroadhesion. Since the implementation of the end</div><div>effector is based entirely on soft materials, the self-sensing magnetically controllable</div><div>electroadhesive gripper (SMEG) can be produced in a simple shape deposition</div><div>manufacturing (SDM) process [2, 3] and is highly applicable to the field of soft</div>robotics [4]. </div></div>

<div>The development of soft materials for various smart applications, such as in</div><div>soft robotic devices derived from elastomers, naturally occurring rubbers and polymers,</div><div>can be traced back to 1940s. Contrary to conventional robotics, soft robotic research</div><div>was primarily dedicated to reproducing and mimicking the elasticity and compliance of</div><div>biological substrates. In the last few decades, however, subsequent progress in soft</div><div>robotic devices and manipulators has been witnessed within the subcategories of</div><div>material & processing, sensor and actuators. In this chapter, a comprehensive</div><div>introduction to soft robotics engineering is highlighted exclusively from the perspective</div><div>of materials development. Soft material prototypes are eventually exploited towards</div><div>designing biomimetic prosthetic devices with sensing capabilities and soft actuating</div><div>bodies. We present an elaborate discussion on soft materials engineering, including</div><div>elastomers, polymer composites containing fillers and associated processing</div><div>methodologies. Despite high flexibility and inherent biocompatibility, conventional</div><div>soft elastomer-based (silicone and polyurethane) matrices often suffer from either poor</div><div>mechanical strength or reduced mechanical output at higher temperatures. This review</div><div>briefly summarizes and critically discusses the different types of compliant materials,</div><div>i.e. elastomers, fluids, gels and others, which are currently being employed in soft</div><div>robotics. This chapter also highlights new opportunities and paves some potential</div><div>avenues to address several challenges, particularly the ones concerning and soft robotic</div><div>materials. Moreover, utilization of soft rubber for sensors and other applications could</div><div>ameliorate the versatility of soft material applications. Therefore, challenges and future</div><div>direction in soft robotics research have to be explicitly integrated within the subdomain</div><div>of materials development and processing and, therefore, addressed in-depth in this</div><div>chapter, with an emphasis on autonomous soft robotic arms capable of stimuliresponsive</div><div>operations.</div>

Elevating stiffness without compromising compliance and agility is a key problem for soft finger applications, especially for articulate ones. Inspired by human finger, a multijoint soft finger with dual morphing through active/passive variable rigidity is proposed. The fabricated soft finger weighs 27.4 g. Conductive thermoplastic starch polymers (CTPSs) are embedded in a U-shape-joint pneumatic soft actuator segmentally like biological phalanges. Their stiffness can be independently adjusted utilizing customized thermomechanical property. Yoshimura origami imitating ligaments can passively match deformation and stiffness of the joints. Through electrothemal activation of CTPSs, the finger can realize dual independent articulate morphing: stiffened phalanges (mode 1) for dexterous manipulation and heavy load, softened phalanges (mode 2) for large deformation contact and light load. Comparative experiments of bending angle, output force, and stiffness are carried out between the active and passive stiffness adjustment of mode 1 and mode 2. The results show that the output force and stiffness of the finger adopting mode 1 can be improved more than two times and five times, and its compliance using mode 2 is almost similar, compared with the pure soft one. To further demonstrate performances of dual-mode morphing, a three-fingered gripper is assembled for grasping and manipulating targets with different shapes, sizes, rigidity, and weight, including playing card, unshelled raw egg, grapes, and unscrewing the bottle cap. It can successfully lift a dumbbell weighing 1460 g with a 7.6 load/weight ratio through a two-mode switch.

Despite increasing interest in minimally invasive surgical techniques and related developments in flexible endoscopes and catheters, follow-the-leader motion remains elusive. Following the path of least resistance through a tortuous and potentially delicate environment without relying on interaction with the surrounding anatomy requires the control of many degrees of freedom. This typically results in large-diameter instruments. One viable solution to obtain dexterity without increasing size is via multiple-point magnetic actuation over the length of the catheter. The main challenge of this approach is planning magnetic interaction to allow the catheter to adapt to the surrounding anatomy during navigation. We design and manufacture a fully shape-forming, soft magnetic catheter of 80 mm length and 2 mm diameter, capable of navigating a human anatomy in a follow-the-leader fashion. Although this system could be exploited for a range of endoscopic or intravascular applications, here we demonstrate its efficacy for navigational bronchoscopy. From a patient-specific preoperative scan, we optimize the catheters' magnetization profiles and the shape-forming actuating field. To generate the required transient magnetic fields, a dual-robot arm system is employed. We fabricate three separate prototypes to demonstrate minimal contact navigation through a three-dimensional bronchial tree phantom under precomputed robotic control. We also compare a further four separate optimally designed catheters against mechanically equivalent designs with axial magnetization profiles along their length and only at the tip. Using our follow-the-leader approach, we demonstrate up to 50% more accurate tracking, 50% reduction in obstacle contact time during navigation over the state of the art, and an improvement in targeting error of 90%.

Designs of soft actuators are mostly guided and limited to certain target functionalities. This article presents a novel programmable design for soft pneumatic bellows-shaped actuators with distinct motions, thus a wide range of functionalities can be engendered through tuning channel parameters. According to the design principle, a kinematic model is established for motion prediction, and a sampling-based optimal parameter search is executed for automatic design. The proposed design method and kinematic models provide a tool for the generation of an optimal channel curve, with respect to target functions and required motion trajectories. Quantitative characterizations on the analytical model are conducted. To validate the functionalities, we generate three types of actuators to cover a wide range of motions in manipulation and locomotion tasks. Comparisons of model prediction on motion trajectory and prototype performance indicate the efficacy of the forward kinematics, and two task-based optimal designs for manipulation scenarios validate the effectiveness of the design parameter search. Prototyped by additive manufacturing technique with soft matter, multifunctional robots in case studies have been demonstrated, suggesting adaptability of the structure and convenience of the soft actuator's automatic design in both manipulation and locomotion. Results show that the novel design method together with the kinematic model paves a way for designing function-oriented actuators in an automatic flow.

As more roboticists are turning to Nature for design inspiration, it is becoming increasingly apparent that multisystem-level investigations of biological processes can frequently lead to unexpected advances in the development of experimental research platforms. Inspired by these efforts, we present here a holistic approach to developing an autonomous starfish-inspired soft robot that embodies a number of key design, fabrication, and actuation principles. These key concepts include integrated and sequentially deployable magnetic tube feet for site-specific and reversible substrate attachment, individually addressable flexible arms, and highly efficient and self-contained fluidic engines. These individual features offer a level of synergistic motion control not previously seen in other starfish-inspired robots. For example, our bistable dome-like tube feet are capable of achieving high adhesion forces to ferrous surfaces and low removal forces. These tube feet are further integrated with a fluidic engine to drive the entire arm while maintaining the ability to accurately control the arm position with a 270° range of motion. Furthermore, the arm and fluidic engine are modular, allowing each of the five arms to be replaced in seconds or enabling the exploration of a variety of limb geometries. Through the incorporation of these different design elements, the ASTER-bot (named for its star-like body plan) is capable of locomotion on ferrous surfaces, above and below water, and on nonplanar surfaces. This article further describes the design, fabrication, and integration strategies and characterizes the energetic and locomotory performance of this pentaradial robotic prototype.