“Bobbit Worm”‐Inspired Soft Adaptive Grasper with Self‐Generated Triboelectric Force Sensor

Soft actuators can realize delicate adaptive grasping of fragile and irregularly shaped objects, which are essential in biological and engineering systems. Yet, critical concerns in the frontier soft graspers are insufficient grasping ability and functional limitations. Here, we propose a Bobbit worm‐inspired multimodal‐sensing adaptive soft grasper (MSASG) enabled by harnessing the Miura‐origami skeleton integrated with self‐generated triboelectric force sensors (TFSs). The Miura‐origami skeleton endows the soft grasper a high grasping force while provides an energy‐efficient way to passively embrace an object without extra energy input. A multimodal TFSs with tactile sensing (TFS‐1) and pressure‐feedback (TFS‐2) functions is constructed by directly packaging a pyramid‐pattern elastic film on the Miura‐origami skeleton. The MSASG implement fast grasping or releasing action by evaluating pressures of various approaching prey, including hermit crabs, crickets, and beetle, etc. And its sensitivity greater than 0.18 V mN−1. In particular, the grasping performances and triboelectric sensing capacity can be optimized by modulating topological parameters (crease length, and surface film thickness, etc.), using a combination of theoretical modeling, finite element simulations, and experiments. The bionic design of soft graspers broadens the future applications for versatile human‐robot‐environment interaction scenarios, such as adaptive robots, reconfigurable architectures, medical devices, and deep‐sea explorations.


Introduction
[3][4] The unique DOI: 10.1002/adsr.202300154feature of the combination of soft matter and biomimetic motion makes soft robots appealing for various innovative applications where rigid robots fail.However, versatile grasping still faces primary challenges or trade-offs, mainly including stiffness selection, configuration design, and soft gripper multifunctionality.Such features can determine its grasping performance in terms of mechanical compliance, grasping force, and grasping workspace. [5,6]Regarding the first challenge, the graspers must be soft enough to enable desirable conformable contact to complex geometries but stiff enough to support the object's weight. [7,8][12][13][14] For instance, Choi et al. proposed a hardness-variable gripper skin based on magnetorheological elastomer (MRE) technology.The soft MRE skin can switch to a solid-like state reversibly by applying a magnetic field, enabling the gripper to grasp various shaped target objects easily. [15]Inspired by the human finger, Yan et al. proposed an active/passive variable stiffness mechanism in a soft finger to modulate the deformation and load capacity with dual independent morphing. [16]Additionally, particle jamming is another feasible approach to achieving variable stiffness by switching the state of discrete particles between an unjammed, deformable state and a jammed state with solid-like rigidity.Very recently, Yang et al. designed robotic structures with programmable shape changes and stiffness variations by subtly tuning the contacts between discrete trapezoidal particles. [17]Although the stiffness mechanism is typically achieved by using intelligent materials activated by external stimuli, which has been greatly facilitated by recent insights into new soft materials, these regulating strategies have limitations in compatibility, design flexibility, material dependence, robustness and scalability.
An alternate strategy is the geometric design which can provide a general principle for engineering architected mechanisms. [18]Inspired by the Xenia cora arm, Kohls N. et al. designed an entirely soft solenoid actuator with highspeed linear motions. [19]In 2021, Jones et al. employed the continuum mechanics of the bubble casting methodology for fabricating and programming monolithic soft actuators.Upon application of this revolutionary process, soft actuators with different sizes, even the impossible aspect ratios before, have been programmed by rationalizing the rules and tools of out-of-equilibrium fluidic mechanics. [20]Likewise, Wood R.'s group introduced a nondeterministic scheme for soft, adaptable grasping via using a filament-filament array to actively entangle objects with variable geometric and topological parameters. [21][24] For soft grasping, Li et al. proposed a soft gripper architecture with an origami "magic ball" embedded in a flexible membrane driven by a vacuum.This flexible gripper exhibited reliable grasping and manipulation by enveloping all or part of target objects with various geometries. [25]To further improve grasping strength, Liang et al. developed a pneumatic rigid-flexible coupling gripper based on a waterbomb origami mechanism attached with steel sheets to its facets.As expected, the gripper exhibits the desired adaptivity to shape and high load capacity benefiting from the soft waterbomb skeleton and rigid steel sheets, respectively. [26]owever, these rigid components are inaccessible for many soft robotics applications.Intriguingly, a classical Miura-ori unit cell exhibits another interesting aspect of tunable mechanical bistability along the crease patterns, which provides tailored energy barriers/landscape transitions between open/closed motions for passively holding/pinching an object without extra energy input. [27]Very recently, Yasuda et al. proposed a versatile self-adaptive grasping motion based on a leaf-out origami structure featuring bistability and reconfigurability. [28]Liu et al. demonstrated that the performance of flexible grippers can be substantially improved by incorporating simple origami structures (e.g., origami grippers). [29]Inspired by earwig wing, Faber et al. established a spring origami model that broadens the folding design space of traditional origami. [30]Briefly, origami-based grippers can provide powerful grasping performances with inventive opportunities for broadening the scope of soft grasping and manipulation, such as robotic arms, artificial muscles, and metamaterials. [31]However, the grasping workspace for this class of soft graspers is usually limited because most effective grasping is achieved by pneumatic contraction or expansion toward conformal contact. [32]ore importantly, securely grasping typically requires more targets' information, such as the size, shape, and surface/mechanical properties.Thus, an active adaptive grasping integrated with sensing and feedback judgment shows great promise. [33]Biological systems have evolved such adaptive behavior to accommodate the unpredictable, ever-changing environment. [34]Sea anemones can capture prey of different shapes and sizes by self-adaptive changes in their morphology, [35] and the Venus flytrap exhibits a nastic movement response to environmental stimuli. [36]Recent advances in flexible electronics provide a revolutionary strategy for creating such mimic self-adaptive behavior in intelligent soft robots. [37,38]For instance, Qiu et al. developed an artificial Drosera capensis with impressive decision-predation capability for ideal-sized prey by integrating multimodal-sensing and adaptive actuation. [39]As invented in 2012, triboelectric sensors have revolutionized energy harvesting and sensing technology, effectively converting mechanical energy into an electric power/signal in a self-powered motion. [40]Thus, triboelectric mechanical sensors have been employed to real-time monitoring of mechanical disturbances (motion, vibration, pressure, and tactile perception, etc.). [41]ery recently, Zhang et al. established an intrusion detection technology via using a bionic triboelectric nanogenerator sensor, which could capture slight noncontact and contact mechanical disturbances. [42]ionic design has become an innovative paradigm to create multi-functional mechanisms.Since 2017, Bobbitt worms have being broadly recognized owing to their surprising predatory ability revealed in the British broadcasting program "Blue Planet II".They mostly hide in sand exposing five freely-floated antennae to perceive and determine the prey's motion information (e. g. size, distance, etc.), then will leap to capture the optimal prey. [43]Thus, the Bobbitt worm is quite an excellent model to design soft adaptive grasper, which unfortunately is rarely reported.This is mainly due to the technical challenges of combining the required multi-functionality, including perception, grasping action, and feedback, etc., within one integrated body structures.Herein, we propose a Bobbit worm-inspired multimodal-sensing adaptive soft grasper (MSASG) by employing Miura-ori skeleton and self-generated triboelectric force sensors (TFSs) featuring two important advantages: First, the grasping performance is obviously improved.In details, the soft grasper exhibits 11.2fold higher internal stored strain energy than that of the common cantilever structure, which stems from the rigid folding creases in such a Miura-ori skeleton.In this work, the Bobbit worminspired soft grasper, requires not only large grasping force, fast and stable grasping ability, but also delicate grasping to living animals.Compared with flat structure, the Miura-ori structure can provide a large strain energy, enabling the soft materials for strong grasping force.The Miura-ori structure is simultaneously helpful to adjust the grasping workspace by the geometrical adjustment (crease length l, crease angle , etc.).Second, similar to the Bobbit worm, the soft grasper can independently implement multimodal-sensing grasping grasping actions, including grasping and releasing operations.This is because the grasper can perceive and identify the real-time motion information (e. g. pressure) of diverse living organisms benefiting from the selfgenerated triboelectric tactile sensing and pressure-feedback signals.More significantly, the grasping performances and triboelectric property can be optimized by modulating the topological parameters (crease length, crease angle, and surface film thickness, etc.) through evaluating the geometries and weights of targets (hermit crabs, crickets, and beetle, etc.), using a combination of theoretical modeling and experiment.

Conceptual Illustration of the Multimodal-Sensing Adaptive Soft Grasper
Bobbit worms are able to sense and capture prey through their antennas and sharp maxillae, as shown in Figure 1a.For most of the time, they hide their long bodies in the sand with floating five antennae and two sharp maxillae.The antennae are extremely sensitive to the external stimuli, e.g.flow pressure, which can perceive the size and distance of the prey.Once the optimal prey approaches, they will leap to firmly clamp the prey via using their sharp maxillae.Inspired by Bobbit worm, we used the Miura-ori unit cell to construct triboelectric sensory interfaces and realized the multimodal-sensing grasping strategy of a soft grasper (Figure 1b).Specifically, 1) the surface of the Miura-ori skeleton is coated with pyramid-shaped micro-structure Ecoflex film, [44] and the single-electrode mode of TFS-1 is constructed to realize the contact sensing strategy.TFS-1 can generate a voltage signal when a prey contact occurs, so the microcontroller executes the grab command, power on and grasping.2) The cavity of the Miura-ori skeleton is attached to the nitrile layer, and the contact-separation mode of TFS-2 is constructed to realize the pressure feedback strategy.When the prey pressure F p is greater than the elastic force F e , the Ecoflex layer will contact the nitrile layer to trigger TFS-2 so that the control executes the release command, power off and release.
Compared with flat paper, the typical Miura-ori element enables flexible materials to have higher strain energy.Accordingly, we designed MSASG based on the Miura-ori element.It adopts the magnetic drive strategy, [45] which has the advantages of fast response speed and continuous adjustment.It can completely envelop the prey through the origami interior cavity when it is activated, as shown in Figure 2a.Furthermore, the theoretical model of MSASG grasping is established by force analysis.The relationship between grasping force and grasping angle (Figure 2a1), as well as the relationship between grasping force and object information (Figure 2a2) after capture (escape pressure, size, etc.).A theoretical analysis will be discussed in the following sections.

Theoretical Analysis of Grasping Force: Grasping Angle
The Miura-ori unit cell has two basic parameters: the crease length l and the crease angle .The strain energy [46,47] of the unit cell can be modified by adjusting the parameters (Figure S1, Supporting Information).Since the magnetic field inside the inductor coil is non-uniform, the magnetic force changes with the grasping angle .Therefore, we first studied the grasping force-angle relationship during the grasping process.The pullpressure sensor was used to test the magnetic force.The results are shown in Figure 2b.As the grasping angle increased, the magnetic force gradually decreased.In addition, the magnetic force is directly proportional to the current of the inductor coil.Under a current of 1.0 A, when the fulcrum moment balance is taken for a single leaf-liked origami, the grasping force-angle relationship can be given by: where c = √ 2l 2 (1 − cos∠1).The results are shown in Figure 2c.In the actuating process, the grasping force decreases with increasing  and increases with decreasing l.This trend is advantageous because when  is small, the grasper can actuate quickly, and when  is large, the prey can be wrapped with low magnetic energy consumption while also ensuring resistance during an escape.Therefore, MSASG not only captures prey without damage but also ensures the reliability of the grasping.

Theoretical Analysis of Grasping Force: Pressure, Size
The pressure and size of the prey are the key factors affecting the success of the capture.Therefore, the grasping performance of the grasper with different pressures and sizes is analyzed.MSASG can overcome prey gravity and wrap up because of its high strain energy and origami cavities.However, usually the prey will struggle to escape.According to the lever structure, the escape pressure F p of prey is the minimum when it is in the upward direction.The grasping force F n varies with the contact point between the leaf-liked origami and the object.As for the selection of contact points, when the sphere contacts the origami structure, the contact points are located on both sides of the origami structure.When objects of different diameters are in different positions, the contact points are difficult to capture, which causes great obstacles to mechanical analysis.Therefore, we consider simplifying the mechanical model to line contact at the crease (geometric calculation parameters: ∠1 = 130 °and ∠2 = 35 °).When MSASG is closed, the changes in objects' pressure points with different sizes can be obtained through geometric analysis: l 1 = r/tan∠2 ≈ 1.43r.Similarly, the maximum object size when the grasper is completely closed can be obtained as follows: r ≤ l∕( 1tan∠2 + cos ∠1 2 ) ≈ 0.54l.Obviously, the crease length l determines the size of the Miura-ori skeleton, which can grasp larger objects.
In addition, the ability to capture prey can be judged by whether the grasping force of MSASG is greater than the escape pressure of prey, that is, 4F y ≥F p .By taking the moment balance of the fulcrum, the relationship between the grasping force of MSASG and the size of the object and crease length l can be given by: where The theoretical analysis results are shown in Figure 2d.MSASG with crease length l = 15.0 mm can provide higher pressure when capturing small objects.When the crease length l = 17.5 mm, the widest range of target object parameters (pressure and size) can be covered.

Experimental Test of Grasping Force
Finally, the pull-pressure sensor was used to test the grasping force at different grasping angles.Three comparisons between the experimental and theoretical data were made (Figure S2a, Supporting Information).Furthermore, according to the conclusion of the theoretical analysis, the situation of MSASG grasping objects is simulated.The illustration in Figure 2e shows that the pull-pressure sensor is used to test its escape pressure.Pull the ball vertically upward to simulate the escape of the object.Since the theoretical force analysis is based on the steady state of the object, we read the indicator of the moment before the object slides.Specifically, we prepared objects with different diameters and tested the pressure for escape at 1.0 A current (Figure S2b, Supporting Information).The diameter error measured by the micrometer is 1.48%, which is more accurate.
As the diameter of the object increases, the position of the pressure point decreases, and the pressure of the prey that can be captured by MSASG increases accordingly.When the crease length l is reduced, MSASG can grasp prey with a large escape pressure, but its grasping performance decreases quickly when the object diameter increases.The results showed that the experimental data were consistent with the theoretical analysis.In conclusion, MSASG with crease length l = 17.5 mm can capture a larger range of object information (pressure and size) in practical applications.The test accuracy of the pull-pressure sensor is 1 mN.
Further, we designed an experimental test to explore the relationship between crease angle  and grasping workspace.When the crease angle is ≈130°, the maximum grasping workspace of 1.489 cm 3 can be obtained, exhibiting an increase of 112% with that of the plane structure, as shown in Figure S3 (Supporting Information).To explore grasping ability of the origami grasper with large size, we design and fabricate a larger MSASG with an increased crease length from 15 mm to 35 mm (MSASG-35).The prepared MSASG-35 is attached to a robotic arm and its perception and grasping behaviors are explored.As shown in Figure S4 and video media 2 (Video M2, Supporting Information), MSASG-35 can agilely grasp objects with different sizes and weights.The experimental details can be found in Figure S4 (Video M1, M2, Supporting Information).

Design of Structural Parameters of TFS-2
As mentioned above, when a prey moves onto MSASG, TFS-1 will be triggered and the grasping strategy is executed, meanwhile the Ecoflex film on the surface of MSASG will also be deformed under the pressure from the prey.When the prey pressure increases to a critical value, the Ecoflex film will contact with Nitrile layer inside of MSASG.The TFS-2 will be triggered to release the prey.Therefore, the TFS-2 strategy can identify the escape pressure F p of prey and determine grasping or release, thus protecting the organism and the grasper.Then, the prey escape pressure feedback strategy needs to be carefully designed to accurately identify whether the prey is suitable for capture, for example, the trigger threshold of TFS-2 can be equal to the maximum grasping force of MSASG by adjusting the thickness of the mask.A theoretical analysis shows that MSASG with crease length l = 17.5 mm has the best grasping performance and the maximum grasping force F n = 40 mN.
Therefore, the trigger threshold of the pressure feedback strategy TFS-2 was designed according to the grasping force, namely, the elastic force F e of the Ecoflex layer with thickness h when it was in contact with the nitrile layer.
First, when the maximum deformation  = 5 mm, the elastic force F e of the Ecoflex layer is calculated by the fixed beam bending model, as shown in Formula (3): where E is the Young's modulus of Ecoflex, E = 10 kPa, I is the second moment of area, b is the width of the Miura-ori skeleton, b = 10 mm, and c is the length of the Miura-ori skeleton, c≈31.72 mm.Second, if F e = F n = 40 mN, then the thickness of the Ecoflex layer is ≈0.5 mm.In this way, the trigger threshold F e of the pressure feedback strategy is equivalent to the grasping force F n .

Multimodal-Sensing Grasping Performance and Topology Optimization
Figure 3a shows the multimodal-sensing grasping performance of the soft grasper.For soft grasping, we designed a TFS-1 sensor on the surface of MSASG, aiming to perceive moving information of living organisms and implement fast grasping behaviors.
When the hermit crab and beetle move to the soft grasper, TFS-1 generates a voltage signal to wake up the microcontroller circuit, and MSASG quickly captures the prey.MSASG can quickly capture hermit crabs with regular shapes and low pressure and release the prey after steadily grasping them.The capture time of MSASG has been set to 4.0 s, and then automatically release the preys to avoid harming of these living organisms.However, beetles usually have high pressure and can deform the Ecoflex layer.For the protection of MSASG, we designed a TFS-2 sensor inside of MSASG.According to the design criteria of MSASG in terms of maximum elastic deformation, maximum grasping force and organism pressure, when TFS-2 is triggered, the maximum grasping force of MSASG is exceeded, the program will automatically release the organism.thereby releasing the prey in advance and avoiding damage to organisms or graspers.
Figure 3b shows that MSASG can successfully capture beetles by adjusting the design parameters, such as lowering the crease length l to increase the grasping force F n ' and increasing the thickness of the Ecoflex layer h to increase the elastic force F e '.

Working Mode of TFSs
The working modes of the two TFSs are shown in Figure 4a.When TFS-1 is triggered, the grasping strategy is executed; when TFS-2 is triggered, the release strategy is executed.In the experiment, the contact area and dielectric property of different prey will affect the voltage signal level.Therefore, we selected a flat pyramid-shaped micro-structured Ecoflex layer to test its electrical properties when fully in contact with the butterfly specimen and used a 6514 Electrometer for signal acquisition.As shown in Figure 4b, when the object contacts the Ecoflex layer, the TFS-1 voltage output immediately peaks, reaching an average of 9.22 V. Compared with the smooth surface without micro-pyramid structure, the TFS-1 voltage signal can be increased by 239%.The experimental details can be found in Figure S5 (Supporting Information).Table 1 lists the performance of TFSs and other types of some representative tactile sensors in soft graspers.The TFSs can identify at least 0.1 kPa pressure with 1.80 V voltage signal.Therefore, MSASG can sensitive hunting small insects, such as hermit crabs or crickets.In addition, the voltage signal generated by TFSs can be directly collected, identified, and evaluated by STM32 microcontroller, which greatly improve the system integration.
The voltage output of the contact-separated TFS-2 was tested.As shown in Figure 4c, the contact between the Ecoflex layer and the nitrile layer in the cavity could generate an average signal of 3.40 V with stable performance.Figure 4d shows the real-time signal of MSASG when grasping a hermit crab.First, MSASG is in standby mode.When the hermit crab touches it, TFS-1 generates a voltage signal over 1.80 V to wake up the circuit and quickly capture the crab, then release it ≈4.0 s later.To avoid the wrong trigger, the microcontroller will immediately enter standby mode, waiting for the next work.Here, we estimated the power consumption in the working cycle according to the STM32 microcontroller manual.First, we conducted an experimental evaluation of the movement speed of a hermit crab (Figure S5c, Video M4, Supporting Information).Based on this experiment, the shortest working cycle of the grasper is estimated.As shown in Figure 4e, the beach area was 300 cm 2 and a hermit crab was ≈2 cm 2 .The effective monitoring area of MSASG is ≈35 cm 2 .Therefore, a working cycle is calculated to be at least 200 s, in which the working period is 4.0 s.Then, we estimated the power consumption in the working cycle according to the STM32 microcontroller manual:  = (W 1 + W 2 )/W = 17.54%.Compared with continuous operation, the power consumption of MSASG is reduced by 82.46% Turbine flowmeter [ 33] About 5 mL s −1 •mm Diameter:0-140 mm N/A Piezoelectric sensor [ 39] 1.6 V kPa −1 0.1-10 kPa 0.1 kPa: 10 mV Liquid metal sensor [ 44] 0.017 Ω kPa −1 5-30 kPa 5 kPa: △1 Ω * Data obtained from Grasper 1 catching a cricket (10 mN)."N/A" means not available in the related paper.

Experimental Demonstration
The experiment selected three kinds of creatures to test the capture performance: the shy hermit crab, an amphibious organism with a regular geometric shape; a small and agile cricket; and beetles with high pressure.Because of the features of soft adaptive grasping, the prey will not be damaged, so the beetle does not struggle too much.A cage surrounded by Ecoflex film was carefully designed to test the pressure deformation of small ani-mals on the membrane, as shown in Figure 5a.The box was surrounded by 0.5 mm thick Ecoflex film, and the pressure deformation of the film was checked by a beetle.The beetle pressure was calculated by the fixed beam bending model (Figure 5b).At the same time, the pressure required to achieve the same deformation was tested by the pull-pressure sensor (Figure 5c).Because of the different contact areas of the applied pressure, an error of 12.5% was obtained between the experimental and computational data.See video media 5 (Video M5, Supporting Information) for the details of the experiment.Among the other small animals, the hermit crab retreats into its shell when disturbed, and the gripper simply has to overcome its gravity to capture it.For a small cricket, the grasper has a cavity large enough to wrap it, making it difficult to escape.Therefore, the pressure is assessed by gravity.Figure 5d shows the process of grasping hermit crabs (24 mN, as shown in Video M6, Supporting Information).Figure 5e shows that even a small, agile cricket (10 mN) can be successfully grasped (as shown in M7, the output voltage signal of TFS-1 is 1.80 V and the sensitivity Temperature-driven grippers [ 4 ] Yes Soft enveloping gripper [ 8] Yes Yes Soft electromagnetic actuator [ 19] Yes Rigid-flexible coupling gripper [ 26] Yes Yes Yes Leaf-like origami structure [ 28] Yes Yes Biomimetic drosera capensis [ 39] Yes Yes Yes is greater than 18 V kPa −1 ). Figure 5f shows that when the beetle was captured, because of its high escape pressure (80 mN), the feedback strategy was triggered to release in advance.After that, we increased the surface film thickness (from 0.5 mm to 0.7 mm), appropriately reduced the crease length (from 17.5 mm to 15.0 mm), assisted in increasing the current to increase the grasping force and pressure feedback threshold to 110 mN, and successfully captured the beetle for more than 4.0 s (M8).The capture time here is conducive to our subsequent setting of the biological data acquisition strategy for the soft grasper, which can detect the size and pressure data of organisms in unmanned environments and underwater conditions, thus providing data support for the exploration of biological communities in unknown fields.
The grasping performance of the recent advances in various soft graspers has been summarized, including the sensing, multimodal, responsive characteristics, and their grasping ability (in-clude adaptive arbitrary shape and moving animals/objects).As shown in Table 2, our MSASG demonstrates comprehensive advantages in grasping characteristics.It can recognize the realtime moving information (e. g. pressure) of various animals through TFS-1 and TFS-2 pressure sensors, and evaluate the grasping behavior (capture or release) by a programmed multimodal function.In addition, MSASG exhibits the advantages of low energy consumption, miniaturization, programmability and fast response.

Conclusion
In summary, we proposed a Bobbit worm-inspired MSASG employing Miura-ori skeleton integrating with self-generated TFSs.Similar to the hunting process of Bobbit worm, MSASG can implement multimodal-sensing grasping grasping actions via perceiving and evaluating the real-time motion information (e.g., escape pressure) of diverse living organisms.One of MSASG fabricated in our study is only 2.75 g heavy when the crease length is 17.5 mm, while its grasping force and grasping workspace can reach ≈40 mN and 17.5 mm 3 , respectively.Such a MSASG can swiftly capture diverse small living organisms, including hermit crabs (24 mN), and crickets (10 mN), with the sensitivity greater than 0.18 V mN −1 and extremely low energy consumption of 0.514 mJ supplied for the MCU circuit.More significantly, the grasping force can be improved (from 40 mN to 110 mN) via optimizing the crease length (from 17.5 mm to 15 mm) of the Miuraori elements, which can successfully envelop larger creatures, e.g.beetles (80 mN).By virtue of the self-generated TFSs and preciseprogramming wake-up circuits, the grasping process exhibited extremely reduced energy consumption by 82.46%.The scalefree geometric character of Miura-ori element enables MSASG design with extending programmability and scalability.Finally, this bionic design opens the door to develop all-in-one soft actuators integrating with multi-functionality on demand toward extensive applications in biological and engineering systems.

Experimental Section
Fabrication Process of TFS-2: First, by drawing a 2D sketch of the origami structure, the PA6 film was quickly cut into shape with a laser cutting machine, as shown in Figure 6a.The origami structures and circular connecting pieces were obtained.Four Miura-ori skeletons were folded by the origami structures and assembled on the connecting piece, then bonded with the magnetic core.Second, TFS-2 consists of nitrile layer and Al electrode.The nitrile layer and Al tape were pasted into the cavity of the Miura-ori skeleton, and the TFS-2 signal was drawn out through copper wire.
Fabrication Process of TFS-1: TFS-1 consists of micro-pyramid Ecoflex layer.As shown in Figure 6b, part-A and part-B of Ecoflex-0020 were mixed 1:1 for 10 min and then poured onto the inverted pyramid-microstructure mold to scratch the film (micro-pyramid mold prepared by FDM 3D printing).After vacuum degassing for 10 min and room temperature curing for 1 h, the micro-pyramid layer was prepared.The design shape was also obtained by laser cutting.Similarly, TFS-1 signal was extracted with an Al electrode in the center of Ecoflex layer.Finally, as shown in Figure 6c, the Ecoflex layer was bonded with the four skeletons and assembled with the inductance coil to obtain MSASG.
Statistical Analysis: The original data derived from the TFSs signals test were smoothed and denoised with the savitzky-golay method using the software of Origin 2021.The data were fitted with a 2-order polynomial for every 100 adjacent points.

Figure 2 .
Figure 2. Theoretical results on the grasping performance of the soft grasper.a) Grasping behavior of MSASG and analysis of the grasping force.b) Relationship between the magnetic force and grasping angle.c) Relationship between the grasping force and grasping angle.d) Theoretical relationship between the crease length l of MSASG and the information (pressure, size) of objects.e) Experimental test curve of MSASG crease length l and object information (pressure, size).

Figure 3 .
Figure 3. Multimodal-sensing grasping performance and topology optimization.a) Multimodal-sensing grasping strategy mechanism of MSASG.b) Topology optimization of MSASG to capture beetle.

Figure 4 .
Figure 4. Working modes of the TFSs.a) Scheme of the perception and force-feedback strategies.b) The TFS-1 voltage output in single-electrode mode.c) The TFS-2 voltage output in contact-separation mode.d) Signal changes at different stages during the capture of hermit crabs by MSASG.

Figure 5 .
Figure 5. Experimental application demonstration of MSASG.a) Experimental test device for beetle escape pressure.b) Fixed beam model for calculating the beetle escape pressure.c) Sensor test of beetle escape pressure.d) Grasping process of a hermit crab on a sandy beach.e) Grasping process of a cricket on grassland.f) Multimodal-sensing grasping process of a beetle on grassland.

Figure 6 .
Figure 6.Scheme of the preparation of MSASG.a) Laser cutting preparation of the Miura-ori skeleton and assembly of TFS-2.b) Preparation scheme of TFS-1.c) Overall assembly of MSASG.

Table 1 .
The comparisons of performances of some representative tactile sensors in soft graspers.

Table 2 .
Comparisons of the soft robotic graspers.