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Soft robotic hands with laser patterned Kirigami sensor network. To enhance the sensing ability of a soft robotic hand (Soft Robotics Inc.), a sensor network is embedded in a transparent silicone skin and stretched around it. a Image of the sensor network on a soft robotic finger. b, c Network accommodates large bending deflections, as shown in Supplementary Movie 1 and 2. d Magnified view of a thermal sensing unit (130 μm wide traces × 330 mm trace length) and stretchable interconnects (40-250 μm wide traces × 30 mm trace length) (e). Detail of interconnects embedded in a silicone skin.
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Soft robotic hands can facilitate human–robot interaction by allowing robots to grasp a wide range of objects safely and gently. However, their performance has been hampered by a lack of suitable sensing systems. We present a flexible and stretchable multi-modal sensor network integrated with a soft robotic hand. The design of wired sensors on a fl...
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... By controlling the power of a UV laser, we can both create sensor patterns, ablating metal without damaging the plastic beneath, and then cut the film to create highly stretchable interconnects. We fabricated a robotic skin that consists of sensors connected by Kirigami wire traces, expanded and embedded in soft and stretchable silicone rubber (Fig. 1a). The skin is then stretched and wrapped around the soft fingers to keep it attached without wrinkles as the fingers flex and extend (Fig. 1b, ...
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... the film to create highly stretchable interconnects. We fabricated a robotic skin that consists of sensors connected by Kirigami wire traces, expanded and embedded in soft and stretchable silicone rubber (Fig. 1a). The skin is then stretched and wrapped around the soft fingers to keep it attached without wrinkles as the fingers flex and extend (Fig. 1b, ...
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... example network, shown in Fig. 1a, consists of 4 temperature sensors and 4 proximity sensors with interconnects that provide 8 signals and 2 ground wires routed to the backs of the fingers. The sensors occupy discrete pads (Fig. 1d) that are flexible but not locally stretchable (maximum strain is 0.03, with impedance change of <0.01% for 60 cyclic tests.). Stretching ...
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... example network, shown in Fig. 1a, consists of 4 temperature sensors and 4 proximity sensors with interconnects that provide 8 signals and 2 ground wires routed to the backs of the fingers. The sensors occupy discrete pads (Fig. 1d) that are flexible but not locally stretchable (maximum strain is 0.03, with impedance change of <0.01% for 60 cyclic tests.). Stretching occurs in the serpentine interconnects (Fig. 1e), which expand without substantially affecting sensor readings. The serpentine connectors can contain multiple conductive traces, which is useful for ...
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... sensors and 4 proximity sensors with interconnects that provide 8 signals and 2 ground wires routed to the backs of the fingers. The sensors occupy discrete pads (Fig. 1d) that are flexible but not locally stretchable (maximum strain is 0.03, with impedance change of <0.01% for 60 cyclic tests.). Stretching occurs in the serpentine interconnects (Fig. 1e), which expand without substantially affecting sensor readings. The serpentine connectors can contain multiple conductive traces, which is useful for connecting multiple sensors to an analog-to-digital converter ...
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Damage detection is one of the critical challenges in operating soft robots in an industrial setting. In repetitive tasks, even a small cut or fatigue can propagate to large damage ceasing the complete operation process. Although research has shown that damage detection can be performed through an embedded sensor network, this approach leads to com...
Citations
... In the realm of artificial electronics, significant efforts have been directed toward implementing adaptive capabilities 8,9 . These efforts have predominantly focused on developing centralized control systems that utilize additional controllers to interface with separate sensing and actuation modules [10][11][12][13][14][15] . However, these components, produced from different materials and processing techniques, are typically manufactured independently. ...
Achieving adaptive behavior in artificial systems, analogous to living organisms, has been a long-standing goal in electronics and materials science. Efforts to integrate adaptive capabilities into synthetic electronics traditionally involved a typical architecture comprising of sensors, an external controller, and actuators constructed from multiple materials. However, challenges arise when attempting to unite these three components into a single entity capable of independently coping with dynamic environments. Here, we unveil an adaptive electronic unit based on a liquid crystal polymer that seamlessly incorporates sensing, signal processing, and actuating functionalities. The polymer forms a film that undergoes anisotropic deformations when exposed to a minor heat pulse generated by human touch. We integrate this property into an electric circuit to facilitate switching. We showcase the concept by creating an interactive system that features distributed information processing including feedback loops and enabling cascading signal transmission across multiple adaptive units. This system responds progressively, in a multi-layered cascade to a dynamic change in its environment. The incorporation of adaptive capabilities into a single piece of responsive material holds immense potential for expediting progress in next-generation flexible electronics, soft robotics, and swarm intelligence.
... Researchers have demonstrated the capability to remotely instruct a soft robotic arm to complete operational tasks without touching it and without wearing any devices, achieving this through air-gesture teaching. Building on this, Ham, J also developed a sensor (BSFS) that operates in both non-contact and tactile modes for a soft robotic arm, based on triboelectric nanogenerators and the giant magneto strictive effect [49]. This dual-mode sensor is used to detect the physical characteristics of target objects, such as shape, material, and surface roughness. ...
Soft robotics is closely related to embodied intelligence in the joint exploration of the means to achieve more natural and effective robotic behaviors via physical forms and intelligent interactions. Embodied intelligence emphasizes that intelligence is affected by the synergy of the brain, body, and environment, focusing on the interaction between agents and the environment. Under this framework, the design and control strategies of soft robotics depend on their physical forms and material properties, as well as algorithms and data processing, which enable them to interact with the environment in a natural and adaptable manner. At present, embodied intelligence has comprehensively integrated related research results on the evolution, learning, perception, decision making in the field of intelligent algorithms, as well as on the behaviors and controls in the field of robotics. From this perspective, the relevant branches of the embodied intelligence in the context of soft robotics were studied, covering the computation of embodied morphology; the evolution of embodied AI; and the perception, control, and decision making of soft robotics. Moreover, on this basis, important research progress was summarized, and related scientific problems were discussed. This study can provide a reference for the research of embodied intelligence in the context of soft robotics.
... A proximity sensor network fabricated by patterning two interdigitated comb electrodes is presented in Ham et al. (2022). As a conductive object approaches, a fringe field is generated between electrodes. ...
... A flexible bimodal smart skin (FBSS) based on triboelectric nanogenerators and liquid metal sensing that can perform simultaneous tactile and touchless sensing and distinguish these two modes in real-time (Liu W. et al., 2022) is a multimodal teachable soft interface that reacts to both touch and touchless stimuli. The soft robotic skin made with a laserpatterned kirigami structure of a sensor network was applied on a soft gripper (Ham et al., 2022). This includes both proximity and temperature sensing, which uses the changes in capacitance and resistance, respectively. ...
... The choice of fabrication method will depend on (2022) touch Liu et al. (2022b) magnetism Cañón Bermúdez et al. (2018) the specific application and the desired level of sensitivity and accuracy. For instance, laser ablation strategy and plastic cutting have been used to stretch an expandable multi-modal sensor network around a soft skin (Ham et al., 2022). MEMS are another technology supporting soft structures that not only simplifies sensor architecture for fabrication but also avoids interference from non-relevant objects (Ge et al., 2019). ...
Soft robots are characterized by their mechanical compliance, making them well-suited for various bio-inspired applications. However, the challenge of preserving their flexibility during deployment has necessitated using soft sensors which can enhance their mobility, energy efficiency, and spatial adaptability. Through emulating the structure, strategies, and working principles of human senses, soft robots can detect stimuli without direct contact with soft touchless sensors and tactile stimuli. This has resulted in noteworthy progress within the field of soft robotics. Nevertheless, soft, touchless sensors offer the advantage of non-invasive sensing and gripping without the drawbacks linked to physical contact. Consequently, the popularity of soft touchless sensors has grown in recent years, as they facilitate intuitive and safe interactions with humans, other robots, and the surrounding environment. This review explores the emerging confluence of touchless sensing and soft robotics, outlining a roadmap for deployable soft robots to achieve human-level dexterity.
... Ham et al. 139 reported a multisensory pneumatic soft gripper integrated with a proximity and temperature network, as shown in Figure 8a. This multimodal sensor network was fabricated on a flexible metalized film, and the electrodes were designed in a Kirigami fashion to improve their stretchability. ...
Soft robotics is an exciting field of science and technology that enables robots to manipulate objects with human-like dexterity. Soft robots can handle delicate objects with care, access remote areas, and offer realistic feedback on their handling performance. However, increased dexterity and mechanical compliance of soft robots come with the need for accurate control of the position and shape of these robots. Therefore, soft robots must be equipped with sensors for better perception of their surroundings, location, force, temperature, shape, and other stimuli for effective usage. This review highlights recent progress in sensing feedback technologies for soft robotic applications. It begins with an introduction to actuation technologies and material selection in soft robotics, followed by an in-depth exploration of various types of sensors, their integration methods, and the benefits of multimodal sensing, signal processing, and control strategies. A short description of current market leaders in soft robotics is also included in the review to illustrate the growing demands of this technology. By examining the latest advancements in sensing feedback technologies for soft robots, this review aims to highlight the potential of soft robotics and inspire innovation in the field.
... This test is designed to observe the performance of STicker as a stretchable solder by placing it in an extreme condition. Unlike general stretching tests performed for stretchable conductor researches, [14][15][16] STicker is laid between, or solders, two non-stretchable, or rigid, conductors with an infinitesimal gap where the conductors are initially in an open state, as demonstrated in Figure 2a-i. When two conductors soldered by STicker are stretched, STicker is under theoretically infinite strain (≡∆L/L, where L is the initial distance or gap between two conductors) since its initial distance is zero (an infinitesimal gap between two conductors, or L→0). ...
Researchers are eagerly developing various stretchable conductors to fabricate devices for next‐generation electronics. Most of the major problems in stretchable electronics happen at the connection between rigid and soft parts and the development of reliable soldering material is a major hurdle in stretchable electronics. Though there are attempts to devise new soldering processes for integrating chips and stretchable conductors, they still possess limitations such as mechanical stability, mass production, sophisticated processes, and restricted candidates for conductors and substrates. Here, this study presents a room‐temperature universal stretchable sticker‐like soldering process that can stretchably solder multiple spots at once and directly fabricates a stretchable device in an in situ manner while a target conductor is installed on one's body. The solder developed in this research possesses high conductivity with a unique freestanding feature enabling the process. It can be elongated when directly positioned between a rigid chip and a rigid conductor, demonstrating its extraordinary stretchability. It is expected that this simple but unique stretchable soldering technique utilizing the invented solder will allow the integration of functional stretchable conductors with highly advanced rigid chips for next‐generation stretchable electronics.
... The primary purpose of this adjustment is to search for a proper grasping position or relocate the grasped target [6] . In the stage of pre-grasping, researchers can use vision or proximity sensors to roughly estimate the object shape and pose [152,153] , which assists in choosing a proper grasping gesture that matches the target object, and an initial grasping position is estimated to reduce the torsional load to the grasping manipulator. Then tentative grasping is conducted and the object pose and inertial parameters are revised through tactile information, which can further adjust the grasping gesture and minimize torsional load [140] . ...
The robotic with integrated tactile sensors can accurately perceive contact force, pressure, vibration, temperature and other tactile stimuli. Flexible tactile sensing technologies have been widely utilized in intelligent robotics for stable grasping, dexterous manipulation, object recognition and human-machine interaction. This review presents promising flexible tactile sensing technologies and their potential applications in robotics. The significance of robotic sensing and tactile sensing performance requirements are first described. The commonly used six types of sensing mechanisms of tactile sensors are briefly illustrated, followed by the progress of novel structural design and performance characteristics of several promising tactile sensors, such as highly sensitive pressure and tri-axis force sensor, flexible distributed sensor array, and multi-modal tactile sensor. Then, the applications of using tactile sensors in robotics such as object properties recognition, grasping and manipulation, and human-machine interactions are thoroughly discussed. Finally, the challenges and future prospects of robotic tactile sensing technologies are discussed. In summary, this review will be conducive to the novel design of flexible tactile sensors and is a heuristic for developing the next generation of intelligent robotics with advanced tactile sensing functions in the future.
In recent years, flexible devices have been highly prized for their lightweight, stretchable, foldable and other excellent properties, and have seen rapid development in daily life. “Learning from nature” drives...
Soft robots have recently attracted increasing interest due to their advantages in durability, flexibility, and deformability, which enable them to adapt to unstructured environments and perform various complex tasks. Perception is crucial for soft robots. To better mimic biological systems, sensors need to be integrated into soft robotic systems to obtain both proprioceptive and external perception for effective usage. This review summarizes the latest advancements in flexible sensing feedback technologies for soft robotic applications. It begins with an introduction to the development of various flexible sensors for soft robots, followed by an in‐depth exploration of smart materials and advanced manufacturing methods. A detailed description of flexible sensing modalities and methodologies is also included in the review to illustrate the continuous breakthrough of the technology. In addition, the applications of soft robots based on these advanced sensing technologies are concluded as well. The challenges of flexible sensing technologies for soft robots and promising solutions are finally discussed and analyzed to provide a prospect for future development. By examining the recent advances in intelligent flexible sensing technologies, this review is dedicated to highlighting the potential of soft robotics and motivating innovation within the field.
