Researchers of the Integrated Systems Engineering Group of the University of Malaga (UMA) have designed a telepresence robot that enables people suffering from COVID-19 to talk to their loved ones.

Spending on global offshore renewable energy infrastructure over the next ten years is expected to reach over US$16 billion (£11.3bn). This involves creating an extra 2.5 million kilometers of global submarine cables by 2030.

Retrofit machines can bring legacy devices into the Internet of Things. Sensors and digital controls provide valuable information and integrate older machines into new, intelligent factory management systems.

Agility Robotics, a branch of Oregon State University, has just revealed a new bipedal robot called Cassie. Unlike the many four-legged and four-wheeled robots currently in existence, Cassie will walk much more like a human. This kind of movement allows for far easier travel across diverse types of terrain while delivering packages or even contributing to disaster relief efforts.

A team of researchers at Yale University has developed a new kind of algorithm to improve the functionally of a robot hand. In their paper published in the journal Science Robotics, the group describes their algorithm and then demonstrate, via videos, how it can be used.

By Clara Marc

There is strength in numbers. That’s true not only for humans, but for drones too. By flying in a swarm, they can cover larger areas and collect a wider range of data, since each drone can be equipped with different sensors.

Preventing drones from bumping into each other
One reason why drone swarms haven’t been used more widely is the risk of gridlock within the swarm. Studies on the collective movement of animals show that each agent tends to coordinate its movements with the others, adjusting its trajectory so as to keep a safe inter-agent distance or to travel in alignment, for example.

“In a drone swarm, when one drone changes its trajectory to avoid an obstacle, its neighbors automatically synchronize their movements accordingly,” says Dario Floreano, a professor at EPFL’s School of Engineering and head of the Laboratory of Intelligent Systems (LIS). “But that often causes the swarm to slow down, generates gridlock within the swarm or even leads to collisions.”

Not just reacting, but also predicting
Enrica Soria, a PhD student at LIS, has come up with a new method for getting around that problem. She has developed a predictive control model that allows drones to not just react to others in a swarm, but also to anticipate their own movements and predict those of their neighbors. “Our model gives drones the ability to determine when a neighbor is about to slow down, meaning the slowdown has less of an effect on their own flight,” says Soria. The model works by programing in locally controlled, simple rules, such as a minimum inter-agent distance to maintain, a set velocity to keep, or a specific direction to follow. Soria’s work has just been published in Nature Machine Intelligence.

With Soria’s model, drones are much less dependent on commands issued by a central computer. Drones in aerial light shows, for example, get their instructions from a computer that calculates each one’s trajectory to avoid a collision. “But with our model, drones are commanded using local information and can modify their trajectories autonomously,” says Soria.

A model inspired by nature
Tests run at LIS show that Soria’s system improves the speed, order and safety of drone swarms in areas with a lot of obstacles. “We don’t yet know if, or to what extent, animals are able to predict the movements of those around them,” says Floreano. “But biologists have recently suggested that the synchronized direction changes observed in some large groups would require a more sophisticated cognitive ability than what has been believed until now.”

References

• PAPER – Predictive control of aerial swarms in cluttered environments. Soria, E., Schiano, F. and Floreano, D., Nat Mach Intell (2021). DOI: 10.1038/s42256-021-00341-y

The models that robots use to do tasks work well in the structured environment of the laboratory. Outside the lab, however, even the most sophisticated models may prove inadequate in new situations or in difficult to model tasks, such as working with soft materials like rope and cloth.

Low demand scenarios necessitate a different strategy: tools that can produce more pieces per edge while providing process security. Here, the goal should be fewer production interruptions and the capability to run unmanned production.

Using a robotic 'Third Thumb' can impact how the hand is represented in the brain, finds a new study led by UCL researchers.

The rhythmic motions of hair-like cilia move liquids around cells or propel the cells themselves. In nature, cilia flap independently, and mimicking these movements with artificial materials requires complex mechanisms. Now, researchers reporting in ACS Applied Materials & Interfaces have made artificial cilia that move in a wave-like fashion when a rotating magnetic field is applied, making them suitable for versatile, climbing soft robots and microfluidic devices.

Research focusing on swarm robotics typically uses theoretical approaches to describe robotic systems in an abstract way. A theoretical model that is often used in robotics studies is OBLOT, an approach that represents robots as simple systems, all identical, without a memory and unable to communicate with each other.

Last month, Stäubli introduced 5 new models of tool changers to round out our MPS product line. These new models open up much of the smaller payload robots to using tool changers.

This episode is about learning the options you have to get some money to start your startup and what is expected you achieve with that money.

In this podcast series of episodes we are going to explain how to create a robotics startup step by step.

We are going to learn how to select your co-founders, your team, how to look for investors, how to test your ideas, how to get customers, how to reach your market, how to build your product… Starting from zero, how to build a successful robotics startup.

I’m Ricardo Tellez, CEO and co-founder of The Construct startup, a robotics startup at which we deliver the best learning experience to become a ROS Developer, that is, to learn how to program robots with ROS.

Our company is already 5 years long, we are a team of 10 people working around the world. We have more than 100.000 students, and tens of Universities around the world use our online academy to provide the teaching environment to their students.

We have bootstrapped our startup, but we also (unsuccessfully) tried getting investors. We have done a few pivots and finally ended at the point that we are right now.

With all this experience, I’m going to teach you how to build your own startup. And we are going to go through the process by creating ourselves another startup, so you can see in the path how to create your own. So you are going to witness the creation of such robotics startup.

Subscribe to the podcast using any of the following methods

• ROS Developers Podcast on iTunes
• ROS Developers Podcast on Stitcher
• ROS Developers Podcast on Spotify

Or watch the video

The post 94. How to build a robotics startup: getting some money to start appeared first on The Construct.

Machine designers are increasingly asked to build systems that take up less space, operate on less power, and run with higher performance. Thankfully motion controls are answering the call with new motors, new sensors, and new architectures.

On May 14, the National Oceanic and Atmospheric Administration (NOAA) ship Okeanos Explorer will depart from Port Canaveral in Florida on a two-week expedition led by NOAA Ocean Exploration, featuring the technology demonstration of an autonomous underwater vehicle. Called Orpheus, this new class of submersible robot will showcase a system that will help it find its way and identify interesting scientific features on the seafloor.