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In recent years, robots have gained artificial vision, touch, and even smell. “Researchers have been giving robots human-like perception,” says MIT Associate Professor Fadel Adib. In a new paper, Adib’s team is pushing the technology a step further. “We’re trying to give robots superhuman perception,” he says.

Mapping is an essential task in many robotics applications. To build a map, it is frequently assumed that the positions of the robots are a priori unknown and need to be estimated during operation. Multi-robot SLAM is a research direction that addresses the collective exploration and mapping of unknown environments by multi-robot systems. Yet, most results so far have been achieved for small groups of robots. Multi-robot SLAM is still a growing field, and a number of research directions are yet to be explored. Among them, swarm SLAM is an alternative, promising approach that takes advantage of the characteristics of robot swarms.

by   -   March 19, 2021
The new technology pairs wireless sensing with artificial intelligence to determine when a patient is using an insulin pen or inhaler, and it flags potential errors in the patient’s administration method. | Image: courtery of the researchers

From swallowing pills to injecting insulin, patients frequently administer their own medication. But they don’t always get it right. Improper adherence to doctors’ orders is commonplace, accounting for thousands of deaths and billions of dollars in medical costs annually. MIT researchers have developed a system to reduce those numbers for some types of medications.

Nearly all real-world applications of reinforcement learning involve some degree of shift between the training environment and the testing environment. However, prior work has observed that even small shifts in the environment cause most RL algorithms to perform markedly worse. As we aim to scale reinforcement learning algorithms and apply them in the real world, it is increasingly important to learn policies that are robust to changes in the environment.

by   -   February 26, 2021

The ability for humans to generalize their knowledge and experiences to new situations is remarkable, yet poorly understood. For example, imagine a human driver that has only ever driven around their city in clear weather. Even though they never encountered true diversity in driving conditions, they have acquired the fundamental skill of driving, and can adapt reasonably fast to driving in neighboring cities, in rainy or windy weather, or even driving a different car, without much practice nor additional driver’s lessons. While humans excel at adaptation, building intelligent systems with common-sense knowledge and the ability to quickly adapt to new situations is a long-standing problem in artificial intelligence.

A map of the unexplored ocean

Most of the ocean is unknown. Yet we know that the most challenging environments on the planet reside in it. Understanding the ocean in its totality is a key component for the sustainable development of human activities and for the mitigation of climate change, as proclaimed by the United Nations. We are glad to share our perspective about the role of soft robots in ocean exploration and offshore operations at the outset of the ocean decade (2021-2030).

Minimally invasive surgeries in which surgeons gain access to internal tissues through natural orifices or small external excisions are common practice in medicine. They are performed for problems as diverse as delivering stents through catheters, treating abdominal complications, and performing transnasal operations at the skull base in patients with neurological conditions.

Schools of fish exhibit complex, synchronized behaviors that help them find food, migrate, and evade predators. No one fish or sub-group of fish coordinates these movements, nor do fish communicate with each other about what to do next. Rather, these collective behaviors emerge from so-called implicit coordination — individual fish making decisions based on what they see their neighbors doing.

How do honeybees land on flowers or avoid obstacles? One would expect such questions to be mostly of interest to biologists. However, the rise of small electronics and robotic systems has also made them relevant to robotics and Artificial Intelligence (AI). For example, small flying robots are extremely restricted in terms of the sensors and processing that they can carry onboard. If these robots are to be as autonomous as the much larger self-driving cars, they will have to use an extremely efficient type of artificial intelligence – similar to the highly developed intelligence possessed by flying insects.

Drone with event camera

Robotics researchers at the University of Zurich show how onboard cameras can be used to keep damaged quadcopters in the air and flying stably – even without GPS.

The UK Robotics Growth Partnership (RGP) aims to set the conditions for success to empower the UK to be a global leader in Robotics and Autonomous Systems whilst delivering a smarter, safer, more prosperous, sustainable and competitive UK. The aim is for smart machines to become ubiquitous, woven into the fabric of society, in every sector, every workplace, and at home. If done right, this could lead to increased productivity, and improved quality of life. It could enable us to meet Net Zero targets, and support workers as their roles transition from menial tasks.

Sensor sleeve
Graduate student Moritz Graule demonstrates a fabric arm sleeve with embedded sensors. The sensors detect the small changes in the Graule’s forearm muscle through the fabric. Such a sleeve could be used in everything from virtual reality simulations and sportswear to clinical diagnostics for neurodegenerative diseases like Parkinson’s Disease. Credit: Oluwaseun Araromi/Harvard SEAS

By Leah Burrows / SEAS communications

Newly engineered slinky-like strain sensors for textiles and soft robotic systems survive the washing machine, cars and hammers.

Autonomous car identifying objects on the road
If robots could learn from watching demonstrations, your self-driving car could learn how to drive safely by watching you drive around your neighborhood. Photo/iStock.

By Caitlin Dawson

USC researchers have developed a method that could allow robots to learn new tasks, like setting a table or driving a car, from observing a small number of demonstrations.

by   -   November 6, 2020

Tree sensors
Credit: Imperial College London

By Caroline Brogan

Imperial researchers have created drones that can attach sensors to trees to monitor environmental and ecological changes in forests.

by   -   October 31, 2020

By Nicola Nosengo

NCCR Robotics researchers at EPFL have developed a drone with a feathered wing and tail that give it unprecedented flight agility.

Swarms in Space
May 10, 2021

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