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Researchers at Istituto Italiano di Tecnologia (IIT-Italian Institute of Technology) in Genoa has realized a new soft robot inspired by the biology of earthworms, which is able to crawl thanks to soft actuators that elongate or squeeze, when air passes through them or is drawn out.

These systems can be configured and supplied as individual components or as complete integrated motion systems with custom interfaces, cable management solutions, vacuum feedthroughs and application-optimized integrated granite and aluminum structures.

The final episode of our RoboHouse Interview Trilogy: ‘The Working Life of the Robotics Engineer’ interviews Srimannarayana Baratam. Sriman, as he is also called, co-founded the company Perciv.ai just two months after graduating. Rens van Poppel explores his journey so far.

Perciv.ai claims that AI-driven machine perception could become affordable to everyone. When was this vision formed, and how did it come about? Sriman points to the period right after his graduation. He says it was pivotal for building trust with partners, and consensus with effective communication. Because starting your own company comes with a lot of challenges.

 

“It is important for to find partners you can trust,” says Sriman. “You need to understand each other’s motivation and commitment. You need to assess what real value does this person add to the team.”

Coming from an automotive background in India, Sriman’s master’s thesis investigated the use of radar and cameras to protect vulnerable people in urban environments. He co-founded the start-up with his supervisor, Dr András Pálffy, and Balazs Szekeres, another robotics student who heard about the project. In the two months after his graduation, Sriman and his co-founders came together to focus full-time on their vision for Perciv.ai.

“In July and August we sat down and discussed the vision between the three of us,” he says. This period also led to tough conversations, ranging from finance to market strategy. “When finally the main questions were sorted out, you just got to take that leap of faith together. This leap of faith proved fruitful, seeing that the high level of trust resulted in a high level of productivity over the past five months.”

Since then Perciv.ai went on to win the NWO take-off phase 1 grant, got their own office and workspace in RoboHouse, signed a contract with an unmanned aerial vehicle (UAV) company and in doing so, generated their first sales revenue.

“This does not mean that there are no more heavy debates,” Sriman adds. “We all share the same vision, but in order to reach our goal of a sustainable and affordable product, we sometimes have different ideas on what that final product should look like.”

Sriman’s passion for robotics and the company’s goals is palpable: “We want to make machine perception technology available to all.”

The post RoboHouse Interview Trilogy, Part III: Srimannarayana Baratam and Perciv.ai appeared first on RoboHouse.

While robots have become increasingly advanced over the past few years, most of them are still unable to reliably navigate very crowded spaces, such as public areas or roads in urban environments. To be implemented on a large-scale and in the smart cities of the future, however, robots will need to be able to navigate these environments both reliably and safely, without colliding with humans or nearby objects.

Ankle exoskeletons that can help people extend their endurance are a step closer to reality with a new control algorithm, developed at the University of Michigan, that could enable future exoskeletons to automatically adapt to individual users and tasks. This would reduce or eliminate the need for manual recalibration.

Whether you’re designing a fully autonomous, semi-autonomous, or remote-controlled mower, ensure that you are up to date on the safety standards and regulations that apply to your application.

Amazon has identified a financially beneficial way for robots and humans to coexist, and it's saving the online enterprise half a billion dollars per year. Using robots to bring shelves of inventory to associates to pick customer orders cuts down the distance traveled by robots and decreases the company's storage footprint.

For autonomous cars to be able to navigate, their optic sensors—like cameras and laser—require a clear view. Now, researchers at Örebro University have successfully improved the precision in radar sensors for navigation to such a degree that the sensors can be used in autonomous cars, making them for safe driving whatever the weather.

Fulfil’s robot-powered automated store enables The Save Mart Companies to delight customers with accurate grocery orders packed and delivered fast and at ultra-low cost

A tiny robot that could one day help doctors perform surgery was inspired by the incredible gripping ability of geckos and the efficient locomotion of inchworms.

Claire chatted to Dr Jonathan Aitken from the University of Sheffield all about manufacturing, sewer inspection, and robots in the real world.

Jonathan Aitken is a Senior University Teacher in Robotics at the University of Sheffield. His research is focused on building useful, useable, and expandable architectures for future robotics systems. Most recently this has involved building complex digital twins for collaborative robots in manufacturing processes and investigating localisation for robots operating in sewer pipes. His teaching focuses on providing students with the tools to bring distributed computing to complex robotic processes.

Octopus arms coordinate nearly infinite degrees of freedom to perform complex movements such as reaching, grasping, fetching, crawling, and swimming. How these animals achieve such a wide range of activities remains a source of mystery, amazement, and inspiration. Part of the challenge comes from the intricate organization and biomechanics of the internal muscles.

A team of scientists has developed electronic skin that could pave the way for soft, flexible robotic devices to assist with surgical procedures or aid people's mobility.

The conventional deep learning model is a supervised model. It takes months of time to develop and train the model before it is ready for the production line.

Over the past year, images from Ukraine have often portrayed a war resembling other conflicts from the past half-century. Russian forces deploy tanks, fighter planes, warships, amphibious vehicles and attack helicopters. Ukrainians fight back with anti-tank weapons, grenade launchers and anti-aircraft missiles. This is how much of the war appears on the ground.