Title: Human Centered Robot Learning

Abstract: Interactive Learning opens new opportunities for humans to teach robots new tasks. However, several challenges at the intersection of machine-learning and human-robot interaction are raised by the development of interactive learning algorithms and systems. To address such challenges, human-centered AI approaches have to be considered. In this talk, we will show how such approaches could be applied to develop better human centered robot learning algorithms.

Title: Action, Perception and beyond for Cognitive Robotics

Abstract: Enabling robots to “see the world through our eyes” and act in an understandable way are two fundamental challenges for HRI. Machine learning has proven to be precious in supporting the efforts towards these goals. However, the dynamic nature of human behavior makes it particularly difficult to identify solutions that enable effective mutual understanding and collaboration with robots over longer periods of time. An architectural vision, combining action and perception with other important elements such as memory, internal motivations and different types of learning could represent a pathway to more autonomous robots, able to adapt to our needs and “grow” with us, while remaining predictable during the interaction.

Title: The Role of Human Behaviour in Building Social Robots

Abstract: Robots are progressively moving out from research laboratories into real-world human environments, envisioned to provide companion care for elderly people, teach children with special needs, assist people in their day-to-day tasks at home or work, and offer service in public spaces. All these practical applications require that humans and robots work together in human environments, where interaction is unavoidable. Therefore, there has been an increasing effort towards advancing the perception and interaction capabilities of robots, making them recognise, adapt to, and respond to human behaviours and actions, with increasing levels of autonomy. Given this context, in this talk, I will give an overview of our ongoing research activities on the understanding and generation of human behaviour from a robotics perspective. Particularly, I will present examples from our ongoing work on how to make robots navigate in crowded social spaces, learn new tasks by just watching humans, and learn how to adapt to their interaction partners. I will conclude by highlighting the challenges and open problems.

Title: Situated Intelligence - New Challenges and Tools

Abstract: Current hardware trends coupled with advances in perception are bringing the world onto the cusp of a new computing paradigm, not so much in terms of where the computation happens (e.g., desktop, cloud, or mobile), but rather in terms of the subject matter of computation: reasoning about the physical everyday world, at human scale, and in real time. This emerging paradigm, sometimes referred to as spatial computing or situated computing, will generate within the next decade a whole new ecosystem of applications, such as mixed-reality systems for task assistance, education, or remote collaboration scenarios; mobile robots in homes or public spaces; cashierless shopping experiences; intelligent factory floors; and many more. In this talk, I will give a broad overview of our group's research on "situated intelligence," in which we aim to bridge the gaps between current perception technologies and the needs of these new applications. I will present some open research challenges and new open-source tools we are developing to make it easier to build systems that can reason about the 3D world (physical or virtual) and collaborate with people in physical space.

Title: Social Signals in the Wild: Multimodal Machine Learning for Human-Robot Interaction

Abstract: Science fiction has long promised us interfaces and robots that interact with us as smoothly as humans do - Rosie the Robot from The Jetsons, C-3PO from Star Wars, and Samantha from Her. Today, interactive robots and voice user interfaces are moving us closer to effortless, human-like interactions in the real world. In this talk, I will discuss the opportunities and challenges in creating technologies that can analyze, detect and generate non-verbal communication, including gestures, gaze, auditory signals, and facial expressions. Specifically, I will discuss how we might allow robots to understand human social signals (including emotions, mental states, and attitudes) across cultures as well as in recognize and generate expressions with diversity in mind.