As robots enter the messy human world so the vital matter of safety takes on a fresh complexion with physical contact becoming inevitable and even desirable. We report on an artistic-exploration of how dancers, working as part of a multidisciplinary team, engaged in contact improvisation exercises to explore the opportunities and challenges of dancing with cobots. We reveal how they employed their honed bodily senses and physical skills to engage with the robots aesthetically and yet safely, interleaving improvised physical manipulations with reflections to grow their knowledge of how the robots behaved and felt. We introduce somatic safety, a holistic mind-body approach in which safety is learned, felt and enacted through bodily contact with robots in addition to being reasoned about. We conclude that robots need to be better designed for people to hold them and might recognise tacit safety cues among people.We propose that safety should be learned through iterative bodily experience interleaved with reflection.

We reappraise the idea of colliding with robots, moving from a position that tries to avoid or mitigate collisions to one that considers them an important facet of human interaction. We report on a soma design workshop that explored how our bodies could collide with telepresence robots, mobility aids, and a quadruped robot. Based on our findings, we employed soma trajectories to analyse collisions as extended experiences that negotiate key transitions of consent, preparation, launch, contact, ripple, sting, untangle, debris and reflect. We then employed these ideas to analyse two collision experiences, an accidental collision between a person and a drone, and the deliberate design of a robot to play with cats, revealing how real-world collisions involve the complex and ongoing entanglement of soma trajectories. We discuss how viewing collisions as entangled trajectories, or tangles, can be used analytically, as a design approach, and as a lens to broach ethical complexity.

We introduce HARPER, a novel dataset for 3D body pose estimation and forecast in dyadic interactions between users and Spot, the quadruped robot manufactured by Boston Dynamics. The key-novelty is the focus on the robot's perspective, i.e., on the data captured by the robot's sensors. These make 3D body pose analysis challenging because being close to the ground captures humans only partially. The scenario underlying HARPER includes 15 actions, of which 10 involve physical contact between the robot and users. The Corpus contains not only the recordings of the built-in stereo cameras of Spot, but also those of a 6-camera OptiTrack system (all recordings are synchronized). This leads to ground-truth skeletal representations with a precision lower than a millimeter. In addition, the Corpus includes reproducible benchmarks on 3D Human Pose Estimation, Human Pose Forecasting, and Collision Prediction, all based on publicly available baseline approaches. This enables future HARPER users to rigorously compare their results with those we provide in this work.

Who wouldn't want a robot to handle all the household drudgery? With recent advances in artificial intelligence and robotics technology, there is growing interest in developing and marketing household robots capable of handling a variety of domestic chores. Tesla is building a humanoid robot, which, according to CEO Elon Musk, could be used for cooking meals and helping elderly people. Amazon recently acquired iRobot, a prominent robotic vacuum manufacturer, and has been investing heavily in the technology through the Amazon Robotics program to expand robotics technology to the consumer market. In May 2022, Dyson, a company renowned for its power vacuum cleaners, announced that it plans to build the U.K.'s largest robotics center devoted to developing household robots that carry out daily domestic tasks in residential spaces.

The sentient Magic Carpet from Aladdin might have a new competitor. While it can't fly or speak, a new tactile sensing carpet from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) can estimate human poses without using cameras, in a step towards improving self-powered personalized healthcare, smart homes, and gaming. Many of our daily activities involve physical contact with the ground: walking, exercising, or resting. These embedded interactions contain a wealth of information that help us better understand people's movements. Previous research has leveraged use of single RGB cameras, (think Microsoft Kinect), wearable omnidirectional cameras, and even plain old off the shelf webcams, but with the inevitable byproducts of camera occlusions and privacy concerns.

The sentient Magic Carpet from Aladdin might have a new competitor. While it can't fly or speak, a new tactile sensing carpet from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) can estimate human poses without using cameras, in a step towards improving self-powered personalized healthcare, smart homes, and gaming. Many of our daily activities involve physical contact with the ground: walking, exercising, or resting. These embedded interactions contain a wealth of information that help us better understand people's movements. Previous research has leveraged use of single RGB cameras, (think Microsoft Kinect), wearable omnidirectional cameras, and even plain old off the shelf webcams, but with the inevitable byproducts of camera occlusions and privacy concerns.

Over the past year schools across the UK have implemented contactless technology to deliver hot school lunches safely and efficiently. But now, as schools return to normal operations, there's a new type of software powering contactless transactions: facial recognition. Pre-order, cashless payments and contactless are just some of the buzzwords we've heard over the past year, especially regarding school payments and the safe delivery of nutritious school meals. Now more than ever, schools are looking to technology for contactless solutions that increase efficiencies. In 2021, CRB Cunninghams, cashless catering, online payment, and identity management solutions provider to education establishments, launched facial recognition software to UK secondary schools.

Contact Tracing has been used to identify people who were in close proximity to those infected with SARS-Cov2 coronavirus. A number of digital contract tracing applications have been introduced to facilitate or complement physical contact tracing. However, there are a number of privacy issues in the implementation of contract tracing applications, which make people reluctant to install or update their infection status on these applications. In this concept paper, we present ideas from Graph Neural Networks and explainability, that could improve trust in these applications, and encourage adoption by people.

As the ripple of COVID-19 careens around the globe, it's forcing humankind to innovate and change the way we work and live. The upside of where we find ourselves right now is that individuals and corporations will be more resilient in a post-COVID-19 world. Here are nine predictions of what our world may look like once we have left the pandemic behind. There was a time not too long ago when we were impressed by touch screens and all they enabled us to do. COVID-19 has made most of us hyper-aware of every touchable surface that could transmit the disease, so in a post-COVID-19 world, it's expected that we'll have fewer touch screens and more voice interfaces and machine vision interfaces. Prior to the pandemic, we saw the rollout of contactless payment options through mobile devices.

As the ripple of COVID-19 careens around the globe, it's forcing humankind to innovate and change the way we work and live. The upside of where we find ourselves right now is that individuals and corporations will be more resilient in a post-COVID-19 world. Here are nine predictions of what our world may look like once we have left the pandemic behind. There was a time not too long ago that we were impressed by touch screens and all they enabled us to do. COVID-19 has made most of us hyper-aware of every touchable surface that could transmit the disease, so in a post-COVID-19 world, it's expected that we'll have fewer touch screens and more voice interfaces and machine vision interfaces. Prior to the pandemic, we saw the rollout of contactless payment options through mobile devices.