Human-centered AI and robotics

Abstract

Robotics has a special place in AI as robots are connected to the real world and robots increasingly appear in humans everyday environment, from home to industry. Apart from cases were robots are expected to completely replace them, humans will largely benefit from real interactions with such robots. This is not only true for complex interaction scenarios like robots serving as guides, companions or members in a team, but also for more predefined functions like autonomous transport of people or goods. More and more, robots need suitable interfaces to interact with humans in a way that humans feel comfortable and that takes into account the need for a certain transparency about actions taken. The paper describes the requirements and state-of-the-art for a human-centered robotics research and development, including verbal and non-verbal interaction, understanding and learning from each other, as well as ethical questions that have to be dealt with if robots will be included in our everyday environment, influencing human life and societies.

A rubric for human-like agents and NeuroAI

“…Since then, a body of work has focused on various relationships between machine learning and AI, writ large and neuroscience. The wide spectrum of long-term visions ranged from the use of deep neural networks in computational neuroscience [27,47], biological attention [48], memory [49,50], navigation [51,52], the mutual interactions between neuroscience and machine learning (ML) [11], neuroscience-inspired AI [8], drawing analogues across mental imagery and deep learning [53], learning to learn or metalearning as prefrontal cortex (PFC) theory [54], followed by considerations of fast and slow RL [55], continual learning [56], human-centred robotics [25] and critical perspectives [10]. While some researchers predominantly focused on importing and testing deep RL methods or large language models (LLMs) as hypotheses for mechanisms in the brain [44,54,57], others brought the focus to the bidirectional interaction of the fields, especially to how neuroscience influences AI [9].…”

“…Third, the dimensions proposed here are not exhaustive and can be expanded to cover varieties of goals and scales (e.g. single neuron versus largescale brain signals) in contemporary psychology and neuroscience [21], embodied approaches to behaviour [22][23][24] and robotics [25]. In the interest of space, most examples will focus on human-oriented studies, missing the wealth of animal-oriented neuroAI research that has been the focus of computational and systems neuroscience [6,9,21,26,27].…”

Comparative analysis of exoskeleton mechanical models with mobile links having maximal mobility degrees, and their generalization for the case of n links

“…The increase of freedom degrees due to growth of computing power and development of control algorithms is one of the current trends in the evolution of mechatronic devices. It becomes possible to use the artificial intelligence methods to control the motion of anthropomorphic mechanism with large number of freedom degrees [1][2][3][4]. Therefore, the study addresses generalization of the considered models for the case of arbitrary finite number of n links.…”