A new aquatic robot inspired by Manta rays has broken the world record for the fastest swimming soft robot. The robot, designed by a team of engineers from North Carolina State University and the University of Virginia, was able to reach speeds of 6.8 body lengths per second. That comes out to a swim speed of 156.4 mm per second or about 0.35 mph. That time blows past the previous record of 3.74 body lengths per second record previously set by the same researchers. Researchers behind the machine, who published their findings today in Science Advances, told Popular Science the new design could be useful for future deep-sea exploration efforts.

Soft robots - due to their intrinsic flexibility of the body - can adaptively navigate unstructured environments. One of the most popular locomotion gaits that has been implemented in soft robots is undulation. The undulation motion in soft robots resembles the locomotion gait of stringy creatures such as snakes, eels, and C. Elegans. Typically, the implementation of undulation locomotion on a soft robot requires many actuators to control each segment of the stringy body. The added weight of multiple actuators limits the navigating performance of soft-bodied robots. In this paper, we propose a simple tendon-driven flexible beam with only one actuator (a DC motor) that can generate a mechanical traveling wave along the beam to support the undulation locomotion of soft robots. The beam will be precompressed along its axis by shortening the length of the two tendons to form an S-shape, thus pretensioning the tendons. The motor will wind and unwind the tendons to deform the flexible beam and generate traveling waves along the body of the robot. We experiment with different pre-tension to characterize the relationship between tendon pre-tension forces and the DC-motor winding/unwinding. Our proposal enables a simple implementation of undulation motion to support the locomotion of soft-bodied robots.

MIT scientists have developed tiny, soft-bodied robots that can be controlled with a weak magnet. The robots, formed from rubbery magnetic spirals, can be programmed to walk, crawl, swim -- all in response to a simple, easy-to-apply magnetic field. "This is the first time this has been done, to be able to control three-dimensional locomotion of robots with a one-dimensional magnetic field," says Professor Polina Anikeeva, whose team published an open-access paper on the magnetic robots in the journal Advanced Materials. "And because they are predominantly composed of polymer and polymers are soft, you don't need a very large magnetic field to activate them. It's actually a really tiny magnetic field that drives these robots," adds Anikeeva, who is a professor of materials science and engineering and brain and cognitive sciences at MIT, a McGovern Institute for Brain Research associate investigator, as well as the associate director of MIT's Research Laboratory of Electronics and director of MIT's K. Lisa Yang Brain-Body Center.

Soft-bodied robots are an extremely important tool in the wider field of robotics, as traditional and rigid-bodied robots are not able to complete the same types of tasks. The former interacts with humans more safely, and they can do things like fit into tight spaces.

There are some tasks that traditional robots -- the rigid and metallic kind -- simply aren't cut out for. Soft-bodied robots, on the other hand, may be able to interact with people more safely or slip into tight spaces with ease. But for robots to reliably complete their programmed duties, they need to know the whereabouts of all their body parts. MIT researchers have developed an algorithm to help engineers design soft robots that collect more useful information about their surroundings. The deep-learning algorithm suggests an optimized placement of sensors within the robot's body, allowing it to better interact with its environment and complete assigned tasks. The advance is a step toward the automation of robot design.

There are some tasks that traditional robots -- the rigid and metallic kind -- simply aren't cut out for. Soft-bodied robots, on the other hand, may be able to interact with people more safely or slip into tight spaces with ease. But for robots to reliably complete their programmed duties, they need to know the whereabouts of all their body parts. MIT researchers have developed an algorithm to help engineers design soft robots that collect more useful information about their surroundings. The deep-learning algorithm suggests an optimized placement of sensors within the robot's body, allowing it to better interact with its environment and complete assigned tasks. The advance is a step toward the automation of robot design.

While robots armored with hard exoskeletons are common, they're not always ideal. Soft-bodied robots, inspired by fish or other squishy creatures, might better adapt to changing environments and work more safely with people. Roboticists generally have to decide whether to design a hard- or soft-bodied robot for a particular task. But that tradeoff may no longer be necessary. Working with computer simulations, MIT researchers have developed a concept for a soft-bodied robot that can turn rigid on demand.

Lots of experimental robots involve a little bit of cheating. Rather than containing all the necessary electronics and energy sources, they have tethers and wires that provide power and control without weighing the robot down or taking up too much internal space. This is especially true for soft-bodied robots, which typically pump air or fluids to drive their motion. Having to incorporate a power source, pumps, and a reservoir of gas or liquid would significantly increase the weight and complexity of the robot. A team from Cornell University has now demonstrated a clever twist that cuts down on the weight and density of all of this by figuring out how to get one of the materials to perform two functions.

Lots of experimental robots involve a little bit of cheating. Rather than containing all the necessary electronics and energy sources, they have tethers and wires that provide power and control without weighing the robot down or taking up too much internal space. This is especially true for soft-bodied robots, which typically pump air or fluids to drive their motion. Having to incorporate a power source, pumps, and a reservoir of gas or liquid would significantly increase the weight and complexity of the robot. A team from Cornell University has now demonstrated a clever twist that cuts down on the weight and density of all of this by figuring out how to get one of the materials to perform two functions.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. Since its epic landing on Mars in 2012, rappelling down to the surface like a robot commando, the Curiosity Mars rover has been one of our favorite robots of all time, and space. Not only it's an impressive piece of engineering, it's also an amazing exploration tool to help humanity answer questions we've been asking ourselves for a very long time, including: Are we alone?