Amphibians adapt their morphologies and motions to accommodate movement in both terrestrial and aquatic environments. Inspired by these biological features, we present PuffyBot, an untethered shape morphing robot capable of changing its body morphology to navigate multiple environments. Our robot design leverages a scissor-lift mechanism driven by a linear actuator as its primary structure to achieve shape morphing. The transformation enables a volume change from 255.00 cm3 to 423.75 cm3, modulating the buoyant force to counteract a downward force of 3.237 N due to 330 g mass of the robot. A bell-crank linkage is integrated with the scissor-lift mechanism, which adjusts the servo-actuated limbs by 90 degrees, allowing a seamless transition between crawling and swimming modes. The robot is fully waterproof, using thermoplastic polyurethane (TPU) fabric to ensure functionality in aquatic environments. The robot can operate untethered for two hours with an onboard battery of 1000 mA h. Our experimental results demonstrate multi-environment locomotion, including crawling on the land, crawling on the underwater floor, swimming on the water surface, and bimodal buoyancy adjustment to submerge underwater or resurface. These findings show the potential of shape morphing to create versatile and energy efficient robotic platforms suitable for diverse environments.

Summary: The authors introduce a novel approach for inferring hidden physical properties of objects (mass and friction), which also allows the system to make subsequent predictions that depend on these properties. They use a black-box generative model (a physics simulator), to perform sampling-based inference, and leverage a tracking algorithm to transform the data into more suitable latent variables (and reduce its dimensionality) as well as a deep model to improve the sampler. The authors assume priors over the hidden physical properties, and make point estimates of the geometry and velocities of objects using a tracking algorithm, which comprise a full specification of the scene that can be input to a physics engine to generate simulated velocities. These simulated velocities then support inference of the hidden properties within an MCMC sampler: the properties' values are proposed and their consequent simulated velocities are generated, which are then scored against the estimated velocities, similar to ABC. A deep network can be trained as a recognition model, from the inferences of the generative model, and also from the Physics 101 dataset directly.

This paper details a significant milestone towards maturing a buoyant aerial robotic platform, or aerobot, for flight in the Venus clouds. We describe two flights of our subscale altitude-controlled aerobot, fabricated from the materials necessary to survive Venus conditions. During these flights over the Nevada Black Rock desert, the prototype flew at the identical atmospheric densities as 54 to 55 km cloud layer altitudes on Venus. We further describe a first-principle aerobot dynamics model which we validate against the Nevada flight data and subsequently employ to predict the performance of future aerobots on Venus. The aerobot discussed in this paper is under JPL development for an in-situ mission flying multiple circumnavigations of Venus, sampling the chemical and physical properties of the planet's atmosphere and also remotely sensing surface properties.

The Duke Robotics Club is proud to present our robot for the 2024 RoboSub Competition: Oogway. Now in its second year, Oogway has been dramatically upgraded in both its capabilities and reliability. Oogway was built on the principle of independent, well-integrated, and reliable subsystems. Individual components and subsystems were tested and designed separately. Oogway's most advanced capabilities are a result of the tight integration between these subsystems. Such examples include a re-envisioned controls system, an entirely new electrical stack, advanced sonar integration, additional cameras and system monitoring, a new marker dropper, and a watertight capsule mechanism. These additions enabled Oogway to prequalify for Robosub 2024.

Underwater soft grippers exhibit potential for applications such as monitoring, research, and object retrieval. However, existing underwater gripping techniques frequently cause disturbances to ecosystems. In response to this challenge, we present a novel underwater gripping framework comprising a lightweight gripper affixed to a custom submarine pod deployable via drone. This approach minimizes water disturbance and enables efficient navigation to target areas, enhancing overall mission effectiveness. The pod allows for underwater motion and is characterized by four degrees of freedom. It is provided with a custom buoyancy system, two water pumps for differential thrust and two for pitching. The system allows for buoyancy adjustments up to a depth of 6 meters, as well as motion in the plane. The 3-fingered gripper is manufactured out of silicone and was successfully tested on objects with different shapes and sizes, demonstrating a maximum pulling force of up to 8 N when underwater. The reliability of the submarine pod was tested in a water tank by tracking its attitude and energy consumption during grasping maneuvers. The system also accomplished a successful mission in a lake, where it was deployed on a hexacopter. Overall, the integration of this system expands the operational capabilities of underwater grasping, makes grasping missions more efficient and easy to automate, as well as causing less disturbance to the water ecosystem.

We present the first free-floating autonomous underwater construction system capable of using active ballasting to transport cement building blocks efficiently. It is the first free-floating autonomous construction robot to use a paired set of resources: compressed air for buoyancy and a battery for thrusters. In construction trials, our system built structures of up to 12 components and weighing up to 100Kg (75Kg in water). Our system achieves this performance by combining a novel one-degree-of-freedom manipulator, a novel two-component cement block construction system that corrects errors in placement, and a simple active ballasting system combined with compliant placement and grasp behaviors. The passive error correcting components of the system minimize the required complexity in sensing and control. We also explore the problem of buoyancy allocation for building structures at scale by defining a convex program which allocates buoyancy to minimize the predicted energy cost for transporting blocks.

Scientists have demonstrated tiny boats that float upside down underneath a levitating layer of liquid in an amazing quirk of physics. Researchers in Paris were investigating the effect of vertical shaking, which can be used to suspend a layer of liquid in mid-air. Not only was the layer of liquid able to float on a suspended cushion of air, but small model boats floated on the bottom surface, thanks to intense air pressure. This counter-intuitive behaviour is a result of the constant vibrations, which change the forces acting on the floating object. This case of'reverse-buoyancy' might have a practical uses in transporting materials through fluids and separating pollutants from water.

Humans have the ability to seamlessly adapt to changes in their environments: adults can learn to walk on crutches in just a few seconds, people can adapt almost instantaneously to picking up an object that is unexpectedly heavy, and children who can walk on flat ground can quickly adapt their gait to walk uphill without having to relearn how to walk. This adaptation is critical for functioning in the real world. Robots, on the other hand, are typically deployed with a fixed behavior (be it hard-coded or learned), allowing them succeed in specific settings, but leading to failure in others: experiencing a system malfunction, encountering a new terrain or environment changes such as wind, or needing to cope with a payload or other unexpected perturbations. The idea behind our latest research is that the mismatch between predicted and observed recent states should inform the robot to update its model into one that more accurately describes the current situation. Noticing our car skidding on the road, for example, informs us that our actions are having a different effect than expected, and thus allows us to plan our consequent actions accordingly (Figure 1).

Like a miniaturized Moby Dick, the pure-white fish wiggles slowly over the reef, ducking under corals and ascending, then descending again, up and down and all around. Its insides, though, are not flesh, but electronics. And its flexible tail flicking back and forth is not made of muscle and scales, but elastomer. The Soft Robotic Fish, aka SoFi, is a hypnotic machine, the likes of which the sea has never seen before. In a paper published today in Science Robotics, MIT researchers detail the evolution of the world's strangest fish, and describe how it could be a potentially powerful tool for scientists to study ocean life.