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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.

 

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.

 

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. 

Abstract Locomotion is a critically important topic for soft actuators and robotics, however, the locomotion applications based on two-way shape memory polymers (SMPs) have not been well explored so far. In this work, a crosslinked poly(ethylene-co-vinyl acetate) (cPEVA)-based two-way SMP is synthesized using dicumyl peroxide (DCP) as the crosslinker. The influence of the DCP concentration on the mechanical properties and the two-way shape memory properties is systematically studied. A Venus flytrap-inspired soft actuator is made by cPEVA, and it is shown that the actuator can efficiently perform gripping movements, indicating that the resultant cPEVA SMP is capable of producing large output force and recovering from large deformations. This polymer is also utilized to make a self-rolling pentagon-shaped device. It is shown that the structure will efficiently roll on a hot surface, proving the applicability of the material in making sophisticated actuators. With introducing an energy barrier, jumping can be accomplished when the stored energy is fast released. Finite element simulations are also conducted to further understand the underlying mechanisms in the complex behavior of actuators based on cPEVA SMP. This work provides critical insights in designing smart materials with external stimulus responsive programmable function for soft actuator applications. 

Soft robotics enriches the robotic functionalities by engineering soft materials and electronics toward enhanced compliance, adaptivity, and friendly human machine. This decade has witnessed extraordinary progresses and benefits in scaling down soft robotics to small scale for a wide range of potential and promising applications, including medical and surgical soft robots, wearable and rehabilitation robots, and unconstructed environments exploration. This perspective highlights recent research efforts in miniature soft robotics in a brief and comprehensive way in terms of actuation, powering, designs, fabrication, control, and applications in four sections. Section 2 discusses the key aspects of materials selection and structural designs for small‐scale tethered and untethered actuation and powering, including fluidic actuation, stimuli‐responsive actuation, and soft living biohybrid materials, as well as structural forms from 1D to 3D. Section 3 discusses the advanced manufacturing techniques at small scales for fabricating miniature soft robots, including lithography, mechanical self‐assembly, additive manufacturing, tissue engineering, and other fabrication methods. Section 4 discusses the control systems used in miniature robots, including off‐board/onboard controls and artificial intelligence‐based controls. Section 5 discusses their potential broad applications in healthcare, small‐scale objects manipulating and processing, and environmental monitoring. Finally, outlooks on the challenges and opportunities are discussed.