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Tensegrity structures made from rigid rods and elastic cables have unique characteristics, such as being lightweight, easy to fabricate, and high load-carrying to weight capacity. In this article, we leverage tensegrity structures as wheels for a mobile robot that can actively change its shape by expanding or collapsing the wheels. Besides the shape-changing capability, using tensegrity as wheels offers several advantages over traditional wheels of similar sizes, such as a shock-absorbing capability without added mass since tensegrity wheels are both lightweight and highly compliant. We show that a robot with two icosahedron tensegrity wheels can reduce its width from 400 to 180 mm, and simultaneously, increase its height from 75 to 95 mm by changing the expanded tensegrity wheels to collapsed disk-like ones. The tensegrity wheels enable the robot to overcome steps with heights up to 110 and 150 mm with the expanded and collapsed configuration, respectively. We establish design guidelines for robots with tensegrity wheels by analyzing the maximum step height that can be overcome by the robot and the force required to collapse the wheel. The robot can also jump onto obstacles up to 300-mm high with a bistable mechanism that can gradually store but quickly release energy. We demonstrate the robot's locomotion capability in indoor and outdoor environments, including various natural terrains, like sand, grass, rocks, ice, and snow. Our results suggest that using tensegrity structures as wheels for mobile robots can enhance their capability to overcome obstacles, traverse challenging terrains, and survive falls from heights. When combined with other locomotion modes (e.g., jumping), such shape-changing robots can have broad applications for search-and-rescue after disasters or surveillance and monitoring in unstructured environments. 

In nature, animals with soft body parts demonstrate remarkable control over their shape, such as an elephant trunk wrapping around a tree branch to pick it up. However, most research on robotic manipulators focuses on controlling the end effector, partly because the manipulator’s arm is rigidly articulated. With recent advances in soft robotics research, controlling a soft manipulator into many different shapes will significantly improve the robot’s functionality, such as medical robots morphing their shape to navigate the digestive system and deliver drugs to specific locations. However, controlling the shape of soft robots is challenging due to their highly nonlinear dynamics that are computationally intensive. In this paper, we leverage a physics-informed, data-driven approach using the Koopman operator to realize the shape control of soft robots. We simulate the dynamics of a soft manipulator using a physics-based simulator (PyElastica) to generate the input-output data, which is then used to identify an approximated linear model based on the Koopman operator. We then formulate the shapecontrol problem as a convex optimization problem that is computationally efficient. Our linear model is over 12 times faster than the physics-based model in simulating the manipulator’s motion. Further, we can control a soft manipulator into different shapes using model predictive control. We envision that the proposed method can be effectively used to control the shapes of soft robots to interact with uncertain environments or enable shape-morphing robots to fulfill diverse tasks. 

Abstract Shape-morphing robots can change their morphology to fulfill different tasks in varying environments, but existing shape-morphing capability is not embedded in a robot’s body, requiring bulky supporting equipment. Here, we report an embedded shape-morphing scheme with the shape actuation, sensing, and locking, all embedded in a robot’s body. We showcase this embedded scheme using three morphing robotic systems: 1) self-sensing shape-morphing grippers that can adapt to objects for adaptive grasping; 2) a quadrupedal robot that can morph its body shape for different terrestrial locomotion modes (walk, crawl, or horizontal climb); 3) an untethered robot that can morph its limbs’ shape for amphibious locomotion. We also create a library of embedded morphing modules to demonstrate the versatile programmable shapes (e.g., torsion, 3D bending, surface morphing, etc.). Our embedded morphing scheme offers a promising avenue for robots to reconfigure their morphology in an embedded manner that can adapt to different environments on demand. 

Perching onto objects can allow flying robots to stay at a desired height at low or no cost of energy. This paper presents a novel passive mechanism for aerial perching onto smooth surfaces. This mechanism is made from a bistable mechanism and a soft suction cup. Different from existing designs, it can be easily attached onto and detached from a surface, but it can also hold a large weight when attached to a surface. Further, the mechanism can still work when the suction cup is not precisely aligned with the surface, alleviating the requirement for precise motion control of flying robots. The attachment and detachment are facilitated by the bistable mechanism, while the strong holding is enabled by a locking mechanism that can disable the bistable mechanism. We conduct experiments to characterize the required forces for successful attachments and detachments. We also equip the perching mechanism onto a quadcopter to demonstrate it can be successfully used for perching onto smooth surfaces (e.g., glass). 

The recent global outbreaks of epidemics and pandemics have shown us that we are severely under-prepared to cope with infectious agents. Exposure to infectious agents present in biofluids ( e.g. , blood, saliva, urine etc. ) poses a severe risk to clinical laboratory personnel and healthcare workers, resulting in hundreds of millions of hospital-acquired and laboratory-acquired infections annually. Novel technologies that can minimize human exposure through remote and automated handling of infectious biofluids will mitigate such risk. In this work, we present biofluid manipulators, which allow on-demand, remote and lossless manipulation of virtually any liquid droplet. Our manipulators are designed by integrating thermo-responsive soft actuators with superomniphobic surfaces. Utilizing our manipulators, we demonstrate on-demand, remote and lossless manipulation of biofluid droplets. We envision that our biofluid manipulators will not only reduce manual operations and minimize exposure to infectious agents, but also pave the way for developing inexpensive, simple and portable robotic systems, which can allow point-of-care operations, particularly in developing nations. 

Perching onto an object (e.g., tree branches) has recently been leveraged for addressing the limited flight time for flying robots. Successful perching needs a mechanical mechanism to damp out the impact and robustly grasp the object. Generally, such a mechanism requires actuation for grasping. In this article, we present a fully passive mechanism without using any actuator: a mechanically intelligent and passive (MIP) gripper that can be used for either aerial perching or grasping. Initially open, the gripper can be closed by the impact force during perching. After closure, if a sufficient mass (e.g., the robot’s mass) is applied, the gripper can switch to a holding state and maintain that state to hold the mass. Once the mass is removed, the gripper can automatically open. We establish static models for the gripper to predict the required forces for successful state transitions. Based on the models, we develop design guidelines for the gripper so that it can be used for different flying robots with different weights. Experiments are conducted to validate the models. Attaching the gripper onto a quadcopter, we demonstrated aerial perching onto rods and aerial grasping rod-like objects. Because the MIP gripper is lightweight (can reach a mass ratio of 0.75% between the gripper and the grasped object for static grasping), we expect it would be well suited for aerial perching or grasping due to the limited payload capability for flying robots.