Detection of damage serves as the initial phase for autonomous healing or adaptation to damage in resilient robots. While signaling the occurrence of damage proves beneficial, the more critical requirement lies in localizing the damage to enable targeted actions. This article introduces a soft, self- healing damage localization sensor capable of detecting damage at four distinct locations using only a pair of measuring points (electrodes). The sensor comprises four resistive links, forming a resistive circuit, and operates by measuring the equivalent resistance between two fixed terminals. Damage occurring to each link induces a distinct change in the value of the equivalent resistance. The system is initially characterized at the material level and subsequently at the sensor level through multiple damage trials (the sensor can restore functionality through on-demand healing, achieved by applying a temperature of 90 degrees C for 30 min). Finally, the sensor is sandwiched between self-healing layers to form a skin. Out of the 16 damage trials conducted on the sensor, in standalone and embedded configurations, 15 successful localizations were observed. Additionally, reducing the number of electrodes enhances the ease of integration of this technology into various robotic applications, such as the palm of robotic hands.

The rising popularity of soft grippers in industry is due to their impressive adaptability. Yet, this adaptability requires flexibility, which often sacrifices grip firmness and complicates sensor integration. This article introduces two additional innovations, variable stiffness and pneumatic sensing, into a FinRay adaptive gripper. The approach and design for incorporating these innovations are guided by requirements outlined by Festo. Regarding this, a layer-jamming-based variable-stiffness skin broadens gripper applications, manipulating objects of varying hardness and weight, while a pneumatic sensor skin detects contact and loss of contact. Both functionalities rely on the airtightness of the skins, which is compromised if damaged. To address this, both the skins and the gripper were crafted using self-healing polymers. The sensing capability and modulated mechanical performance of the gripper were evaluated experimentally and through simulations, and the self-healing ability was assessed by recharacterization after a damage healing. This work showcases the promising synergy between robotics and self-healing materials, demonstrating mutual reinforcement to a highly efficient gripping system.

Soft fiber-reinforced actuators have demonstrated significant potential across various robotics applications. However, the actuation motion in these actuators is typically limited to a single type of motion behavior, such as bending, extending, and twisting. Additionally, a combination of bending with twisting and extending with twisting can occur in fiber-reinforced actuators. This paper presents two novel hybrid actuators in which shape memory alloy (SMA) wires are used as reinforcement for pneumatic actuation, and upon electrical activation, they create a twisting motion. As a result, the hybrid soft SMA-reinforced actuators can select between twisting and bending, as well as twisting and extending. In pneumatic mode, a bending angle of 40° and a longitudinal strain of 20% were achieved for the bending/twisting and extending/twisting actuators, respectively. When the SMA wires are electrically activated by the Joule effect, the actuators achieved more than 90% of the maximum twisting angle (24°) in almost 2 s. Passive recovery, facilitated by the elastic response of the soft chamber, took approximately 10 s. The double-helical reinforcement by SMA wires not only enables twisting in both directions but also serves as an active recovery mechanism to more rapidly return the finger to the initial position (within 2 s). The resulting pneumatic–electric-driven soft actuators enhance dexterity and versatility, making them suitable for applications in walking robots, in-pipe crawling robots, and in-hand manipulation.

Self-healing soft robots show enormous potential to recover functional performance after healing the damages. However, healing in these systems is limited by the recontact of the fracture surfaces. This paper presents for the first time a shape memory alloy (SMA) wire-reinforced soft bending actuator made out of a castor oil-based self-healing polymer, with the incorporated ability to recover from large incisions via shape memory assisted healing. The integrated SMA wires serve three major purposes; (i) Large incisions are closed by contraction of the current-activated SMA wires that are integrated into the chamber. These pull the fracture surfaces into contact, enabling the healing. (ii) The heat generated during the activation of the SMA wires is synergistically exploited for accelerating the healing. (iii) Lastly, during pneumatic actuation, the wires constrain radial expansion and one-side longitudinal extension of the soft chamber, effectuating the desired actuator bending motion. This novel approach of healing is studied via mechanical and ultrasound tests on the specimen level, as well as via bending characterization of the pneumatic robot in multiple damage healing cycles. This technology allows soft robots to become more independent in terms of their self-healing capabilities from human intervention.

The recent introduction of self-healing soft materials in robotics is a major step towards sustainable next generation robots. By manufacturing soft robots out of these smart materials, we integrate a self-healing ability and increase the physical intelligence of these systems. However, the embodied intelligence in the material level needs to be augmented by incorporating assistive mechanisms in the system level with minimized control, enabling healing of damage in different sizes and in diverse working conditions. These assistive mechanisms can provide damage detection, damage closure, healing stimuli providing, health monitoring, or a combination of the previous. In this paper, we present two different mechanisms for an autonomous healing of damages; (i) Embedding a healable heater in a self-healing soft actuator to increase the temperature required for an efficient healing, while it allows detecting the damage and monitoring the health of the system. (ii) Incorporating shape memory alloy wires in a self-heling soft bending actuator, with simultaneous sealing through contraction and heating abilities. Apart from assisting in the healing action, both mechanisms play a part in the actuation of the bending robots as strain limiting elements. These assistive mechanisms will overcome the limitation on the material level, leading to robots that can self-heal in applications outside of laboratories and factories.

Self-healing polymers render their life cycle more sustainable by recovering their properties upon healing. Intrinsic self-healing polymers can be recycled, which further reduces waste production. Yet, despite these intrinsic benefits, several sustain-abi l i t y issues remain largely neglected, including the use of fossil-derived materials, hazardous chemicals, and material management at the end of its life. Herein, we report a series of castor oil-based self-healing elastomers that account for these challenges and show improved mechanical and self-healing capabilities compared to the other bio-based self-healing materials. Castor oil was functionalized using a simple, one-pot, solventless synthesis from renewable resources and cross-linked by Diels-Alder cycloaddition. They can be reprocessed and recycled or hydrolytically degraded at the end of their service life. The mechanical properties of the material s can be tuned (Young's modulus 0.5-20 MPa), with a fracture strain of up to 487%. A fracture strain of 100% could already be recovered after just 60 s at room temperature and 75% of the mechanical properties after just 24 h. By taking advantage of these properties, a sof t pneumatic gripper has been developed, capable of healing autonomously, which is fully recyclable and degradable. Hence, we provide a sustainable alternative for sof t robotic applications and for self-healing elastomers in general .

The variability in the shapes and sizes of objects presents a significant challenge for two-finger robotic grippers when it comes to manipulating them. Based on the chemistry of vitrimers (a new class of polymer materials that have dynamic covalent bonds, which allow them to reversibly change their mechanical properties under specific conditions), we present two designs as 3D-printed shape memory polymer-based shape-adaptive fingertips (SMP-SAF). The fingertips have two main properties needed for an effective grasping. First, the ability to adapt their shape to different objects. Second, exhibiting variable rigidity, to lock and retain this new shape without the need for any continuous external triggering system. Our two design strategies are: 1) A curved part, which is suitable for grasping delicate and fragile objects. In this mode and prior to gripping, the SMP-SAFs are straightened by the force of the parallel gripper and are adapted to the object by shape memory activation. 2) A straight part that takes on the form of the objects by contact force with them. This mode is better suited for gripping hard bodies and provides a more straightforward shape programming process. The SMP-SAFs can be programmed by heating them up above glass transition temperature (54°C) via Joule-effect of the integrated electrically conductive wire or by using a heat gun, followed by reshaping by the external forces (without human intervention), and subsequently fixing the new shape upon cooling. As the shape programming process is time-consuming, this technique suits adaptive sorting lines where the variety of objects is not changed from grasp to grasp, but from batch to batch.

Self-healing polymers can address the damage susceptibility in soft robotics. However, in most cases, their healing requires a heat stimulus, provided by an external device. This letter presents a self-healing soft actuator with an integrated healable flexible heater, functioning as the stimuli-providing system. The actuator is constructed out of thermoreversible elastomers that are crosslinked by the Diels-Alder (DA) reaction, which provides the healing ability. The heater is manufactured from a DA-based composite network filled with 20 wt% carbon black to provide electrically conductive properties for resistive Joule heating. The flexibility of the heater does not compromise the actuator performance upon integration and the self-healing properties of both heater and actuator allow for damage repair. This includes very large damages, as both heater and actuator can recover (near 100%) from being cut completely in two pieces, using Joule heating at 90°C with a bias voltage of about 30 V. The embedded heater avoids the need for external intervention in the healing process, and provides healing quality assessment and a healing on-demand mechanism, paving the way for an optimum healing solution of damage resilient soft robots that require heat as a healing stimulus.

Recent advances in soft continuum robots revealed the need for accurate models, required to develop advanced control strategies. In this article, a general methodology is presented that allows to create an accurate inverse kinematic control based on hyperelastic models, fitted on mechanical material properties. This methodology is based on finite element analysis (FEA) and links the mechanical properties of the material to the simulated behavior of a Pneunet actuator. This procedure is valid for any sort of hyperelastic material used in soft robotics, however, as a case study, a specific material with a self-healing ability is considered. This elastomeric polymer can recover from macroscopic damages without losing its mechanical performances, after undergoing a heat treatment. In this article, an accurate characterization of the mechanical behavior of this material is provided, involving mechanical testing, both in tensile and compression. On this experimental characterization data constitutive laws are fitted, using a FEA simulator. The robustness of this material modeling is shown, refitting the curve for material samples that were exposed to multiple damage-healing cycles. With this obtained constitutive model, a FEA simulation of a bending soft pneumatic actuator is developed. The simulation results are experimentally validated with a dedicated test bench consisting of a pressure control unit and a motion tracking camera. Using this validated model, an inverse kinematic control is developed, including the FEA simulation in the control scheme.

Recent advances in soft robotics in academia have led to the adoption of soft grippers in industrial settings. Due to their soft bending actuators, these grippers can handle delicate objects with great care. However, due to their flexibility, the actuators are prone to out-of-plane deformations upon asymmetric loading. These undesired deformations lead to reduced grasp performance and may cause instability or failure of the grip. While the state-of-the-art contributions describe complex designs to limit those deformations, this work focuses on a complementary path investigating the material distribution. In this paper, a novel bending actuator is developed with improved out-of-plane deformation resistance by optimizing the material distribution in multi-material designs composed of two polymers with different mechanical properties. This is made possible by the strong interfacial strength of Diels-Alder chemical bonds in the used polymers, which have a self-healing capability. A Solid Isotropic Material with Penalization (SIMP) topology optimization is performed to increase the out-of-plane resistance. The actuator is simulated using FEA COMSOL in which the (hyper) elastic materials are simulated by MooneyRivlin models, fitted on experimental uniaxial tensile test data. This multi-material actuator and a reference single material actuator were manufactured and modeled. Via experimental characterization and validation in FEA simulations, it is shown that the actuator out-of-plane stiffness, characterized by the in-plane bending angle and out-of-plane bending angle, can be increased by an optimized multi-material composition, without changing the geometrical shape of the actuator.