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Achieving multicapability in a single soft gripper for handling ultrasoft, ultrathin, and ultraheavy objects is challenging due to the tradeoff between compliance, strength, and precision. Here, combining experiments, theory, and simulation, we report utilizing angle-programmed tendril-like grasping trajectories for an ultragentle yet ultrastrong and ultraprecise gripper. The single gripper can delicately grasp fragile liquids with minimal contact pressure (0.05 kPa), lift objects 16,000 times its own weight, and precisely grasp ultrathin, flexible objects like 4-μm-thick sheets and 2-μm-diameter microfibers on flat surfaces, all with a high success rate. Its scalable and material-independent design allows for biodegradable noninvasive grippers made from natural leaves. Explicitly controlled trajectories facilitate its integration with robotic arms and prostheses for challenging tasks, including picking grapes, opening zippers, folding clothes, and turning pages. This work showcases soft grippers excelling in extreme scenarios with potential applications in agriculture, food processing, prosthesis, biomedicine, minimally invasive surgeries, and deep-sea exploration.

 

Harnessing snapping, an instability phenomenon observed in nature (e.g., Venus flytraps), for autonomy has attracted growing interest in autonomous soft robots. However, achieving self‐sustained snapping and snapping‐driven autonomous motions in soft robots remains largely unexplored. Here, harnessing bistable, ribbon ring‐like structures for realizing self‐sustained snapping in a library of soft liquid‐crystal elastomer wavy rings under constant thermal and photothermal actuation are reported. The self‐sustained snapping induces continuous ring flipping that drives autonomous dancing or crawling motions on the ground and underwater. The 3D, free‐standing wavy rings employ either a highly symmetric or symmetry‐broken twisted shape with tunable geometric asymmetries. It is found that the former favors periodic self‐dancing motion in place due to isotropic friction, while the latter shows a directional crawling motion along the predefined axis of symmetry during fabrication due to asymmetric friction. It shows that the crawling speed can be tuned by the geometric asymmetries with a peak speed achieved at the highest geometric asymmetry. Lastly, it is shown that the autonomous crawling ring can also adapt its body shape to pass through a confined space that is over 30% narrower than its body size.

 

Kirigami, a traditional paper cutting art, offers a promising strategy for 2D-to-3D shape morphing through cut-guided deformation. Existing kirigami designs for target 3D curved shapes rely on intricate cut patterns in thin sheets, making the inverse design challenging. Motivated by the Gauss-Bonnet theorem that correlates the geodesic curvature along the boundary with the Gaussian curvature, here, we exploit programming the curvature of cut boundaries rather than the complex cut patterns in kirigami sheets for target 3D curved morphologies through both forward and inverse designs. The strategy largely simplifies the inverse design. Leveraging this strategy, we demonstrate its potential applications as a universal and nondestructive gripper for delicate objects, including live fish, raw egg yolk, and a human hair, as well as dynamically conformable heaters for human knees. This study opens a new avenue to encode boundary curvatures for shape-programing materials with potential applications in soft robotics and wearable devices.

 

Kirigami, the ancient paper art of cutting, has recently emerged as a new approach to construct metamaterials with novel properties imparted by cuts. However, most studies are limited to thin sheets‐based 2D kirigami metamaterials with specific forms and limited reconfigurability due to planar connection constraints of cut units. Here, 3D modular kirigami is introduced by cutting bulk materials into spatially closed‐loop connected cut cubes to construct a new class of 3D kirigami metamaterials. The module is transformable with multiple degrees of freedom that can transform into versatile distinct daughter building blocks. Their conformable assembly creates a wealth of reconfigurable and disassemblable metamaterials with diverse structures and unique properties, including reconfigurable 1D column‐like materials, 2D lattice‐like metamaterials with phase transition of chirality, as well as 3D frustration‐free multilayered metamaterials with 3D auxetic behaviors and programmable deformation modes. This study largely expands the design space of kirigami metamaterials from 2D to 3D.

 

Soft actuators are typically designed to be inherently stress‐free and stable. Relaxing such a design constraint allows exploration of harnessing mechanical prestress and elastic instability to achieve potential high‐performance soft robots. Here, the strategy of prestrain relaxation is leveraged to design pre‐curved soft actuators in 2D and 3D with tunable monostability and bistability that can be implemented for multifunctional soft robotics. By bonding stress‐free active layer with embedded pneumatic channels to a uniaxially or biaxially pre‐stretched elastomeric strip or disk, pre‐curved 2D beam‐like bending actuators and 3D doming actuators are generated after prestrain release, respectively. Such pre‐curved soft actuators exhibit tunable monostable and bistable behavior under actuation by simply manipulating the prestrain and the biased bilayer thickness ratio. Their implications in multifunctional soft robotics are demonstrated in achieving high performance in manipulation and locomotion, including energy‐efficient soft gripper to holding objects through prestress, fast‐speed larva‐like jumping soft crawler with average locomotion speed of 0.65 body‐length s⁻¹(51.4 mm s⁻¹), and fast swimming bistable jellyfish‐like soft robot with an average speed of 53.3 mm s⁻¹.

 

Periodic spin–orbit motion is ubiquitous in nature, observed from electrons orbiting nuclei to spinning planets orbiting the Sun. Achieving autonomous periodic orbiting motions, along circular and noncircular paths, in soft mobile robotics is crucial for adaptive and intelligent exploration of unknown environments—a grand challenge yet to be accomplished. Here, we report leveraging a closed-loop twisted ring topology with a defect for an autonomous soft robot capable of achieving periodic spin-orbiting motions with programmed circular and re-programmed irregular-shaped trajectories. Constructed by bonding a twisted liquid crystal elastomer ribbon into a closed-loop ring topology, the robot exhibits three coupled periodic self-motions in response to constant temperature or constant light sources: inside-out flipping, self-spinning around the ring center, and self-orbiting around a point outside the ring. The coupled spinning and orbiting motions share the same direction and period. The spinning or orbiting direction depends on the twisting chirality, while the orbital radius and period are determined by the twisted ring geometry and thermal actuation. The flip–spin and orbiting motions arise from the twisted ring topology and a bonding site defect that breaks the force symmetry, respectively. By utilizing the twisting-encoded autonomous flip–spin–orbit motions, we showcase the robot’s potential for intelligently mapping the geometric boundaries of unknown confined spaces, including convex shapes like circles, squares, triangles, and pentagons and concaves shapes with multi-robots, as well as health monitoring of unknown confined spaces with boundary damages.

 

Autonomous maze navigation is appealing yet challenging in soft robotics for exploring priori unknown unstructured environments, as it often requires human-like brain that integrates onboard power, sensors, and control for computational intelligence. Here, we report harnessing both geometric and materials intelligence in liquid crystal elastomer–based self-rolling robots for autonomous escaping from complex multichannel mazes without the need for human-like brain. The soft robot powered by environmental thermal energy has asymmetric geometry with hybrid twisted and helical shapes on two ends. Such geometric asymmetry enables built-in active and sustained self-turning capabilities, unlike its symmetric counterparts in either twisted or helical shapes that only demonstrate transient self-turning through untwisting. Combining self-snapping for motion reflection, it shows unique curved zigzag paths to avoid entrapment in its counterparts, which allows for successful self-escaping from various challenging mazes, including mazes on granular terrains, mazes with narrow gaps, and even mazes with in situ changing layouts.

 

Distributed programmable thermal actuation enables caterpillar-inspired bidirectional locomotion for soft crawling robots. 

Bistable soft swimmers can achieve both high-speed and high-efficient performances comparable to their biological counterparts. 

Soft robots that can harvest energy from environmental resources for autonomous locomotion is highly desired; however, few are capable of adaptive navigation without human interventions. Here, we report twisting soft robots with embodied physical intelligence for adaptive, intelligent autonomous locomotion in various unstructured environments, without on-board or external controls and human interventions. The soft robots are constructed of twisted thermal-responsive liquid crystal elastomer ribbons with a straight centerline. They can harvest thermal energy from environments to roll on outdoor hard surfaces and challenging granular substrates without slip, including ascending loose sandy slopes, crossing sand ripples, escaping from burying sand, and crossing rocks with additional camouflaging features. The twisting body provides anchoring functionality by burrowing into loose sand. When encountering obstacles, they can either self-turn or self-snap for obstacle negotiation and avoidance. Theoretical models and finite element simulation reveal that such physical intelligence is achieved by spontaneously snapping-through its soft body upon active and adaptive soft body-obstacle interactions. Utilizing this strategy, they can intelligently escape from confined spaces and maze-like obstacle courses without any human intervention. This work presents a de novo design of embodied physical intelligence by harnessing the twisting geometry and snap-through instability for adaptive soft robot-environment interactions.