research

Today Matthijs Smakman will defend his doctoral thesis titled “Robots in Education: The Morally Responsible Deployment of Robot Assistants”. Conducted under the supervision of Prof. Dr. Elly Konijn, his empirically grounded research represents a significant milestone in achieving a morally responsible integration of social robots as educational assistants in primary schools. Previous studies have already indicated that the utilization of social robots yields better outcomes compared to traditional educational technologies.

A machine learning model can predict the locations of minerals on Earth—and potentially other planets—by taking advantage of patterns in mineral associations. Science and industry seek mineral deposits to both better understand the history of our planet and to extract for use in technologies like rechargeable batteries.

Exposure to an augmented reality (AR) or virtual reality (VR) environment can cause people to experience cybersickness — a special type of motion sickness with symptoms ranging from dizziness to nausea — and existing research to mitigate the severity of the symptoms often relies upon a one-size-fits-all approach. However, Khaza Anuarul Hoque, an assistant professor in the Department of Electrical Engineering and Computer Science at the University of Missouri, and a team of researchers are working to develop a personalized approach to identifying cybersickness by focusing on the root causes, which can be different for every person.

Bar-Ilan University researchers have shown that brain-inspired shallow neural networks can achieve the same classification success rates as deep learning architectures consisting of many layers and filters, but with less computational complexity. The findings suggest that efficient learning of non-trivial classification tasks can be achieved using shallow feedforward networks, potentially requiring less computational complexity.

MIT researchers have developed an algorithm that enables drones to avoid collisions while working together in the same airspace. The system, known as Robust MADER, is an improved version of the Multiagent Trajectory-Planner, or MADER, which was presented by MIT researchers in 2020.

Stanford and Google researchers have made a new breakthrough n artificial intelligence (AI) by creating “generative agents” that behave in a remarkably human-like way. These agents were programmed to have the ability to communicate with others and their environment, remember and recall information, reflect on observations, and form plans for each day. In essence, they were given the capacity to think and act like humans.

USC Viterbi computer science researchers have developed a system to teach robots how to predict human preferences in assembly tasks. The system, which was a finalist for the best paper award at the ACM/IEEE International Conference on Human-Robot Interaction (HRI), could help robots become more collaborative helpers in manufacturing and everyday life.

Two researchers from Georgia Tech are studying the trust-repair strategies that robots can use when they deceive humans. Kantwon Rogers, a Ph.D. student, and Reiden Webber, an undergraduate in computer science, are researching robot deception in a driving simulation to explore the effectiveness of apologies to repair trust after robots lie.

Researchers at North Carolina State University have demonstrated a caterpillar-like soft robot that can move forward, backward and dip under narrow spaces. The caterpillar-bot’s movement is driven by a novel pattern of silver nanowires that use heat to control the way the robot bends, allowing users to steer the robot in either direction.

Neil Shortland, associate professor in the School of Criminology and Justice Studies at UMass Lowell, is leading a group of researchers studying the use of artificial intelligence to help make difficult decisions.