A Self for robots: core elements and ascription by humans

Modern robotics is interested in developing humanoid robots with meta-cognitive capabilities in order to create systems that have the possibility of dealing efficiently with the presence of novel situations and unforeseen inputs. Given the relational nature of human beings, with a glimpse into the future of assistive robots, it seems relevant to start thinking about the nature of the interaction with such robots, increasingly human-like not only from the outside but also in terms of behavior. The question posed in this abstract concerns the possibility of ascribing the robot not only a mind but a more profound dimension: a Self

Infusion Micro-Pump Development Using MEMS Technology

International audienceDiabetes is a chronic condition that occurs when the pancreas does not produce enough insulin or when the body cannot effectively use the insulin it produces. People having type 1 diabetes require insulin (10% of all diabetics). People with type 2 diabetes can be treated with oral medication, but may also require insulin; 10% of all type 2 diabetics require insulin. Among the actual different methods to administer insulin (syringes, pens and conventional infusion pumps) a possibility to increase infuser performances is offered by the utilization of silicon based MEMS pumps (Micro- Electro Mechanical Systems). The main two pump families are classified as mechanical and non-mechanical pumps. The former contains check-valve, peristaltic, rectification without valves and rotary ones (“Displacement Pumps”) or Ultrasonic and Centrifugal (“Dynamic Pumps”); the latter consists in Pressure, Concentration, Electrical Potential gradients and Magnetic Potential micro-pumps. The micro-pump described here is an electro-mechanical device actuated with a piezoelectric-element and based on MEMS technology, able to minimize size and costs, offering a high precision pharmacological dispense. Three slices are bonded to reach the final results: top and bottom caps and an intermediate SOI. In case of anodic bonding, top and bottom caps are constituted of micromachined borophosphosilicate wafers, whereas in case of metallic bonding three silicon slices are used. The paper deals with the fabrication evolution of the device according to the different items that had to be faced during development: design, fluidic, mechanical and electrical simulations and characterization, safety requirements and final testing. Built-in reliability is ensured by two inner sensors able to detect any occlusion or malfunctioning and informing so the patient. The result is a compact, core pump chip that can deliver from 0.02 Units of insulin up to 3.6 Units per minute with accuracy better than 5%

Spatiotemporal Coordination Supports a Sense of Commitment in Human-Robot Interaction

In the current study, we presented participants with videos in which a humanoid robot (iCub) and a human agent were tidying up by moving toys from a table into a container. In the High Coordination condition, the two agents worked together in a coordinated manner, with the human picking up the toys and passing them to the robot. In the Low Coordination condition, they worked in parallel without coordinating. Participants were asked to imagine themselves in the position of the human agent and to respond to a battery of questions to probe the extent to which they felt committed to the joint action. While we did not observe a main effect of our coordination manipulation, the results do reveal that participants who perceived a higher degree of coordination also indicated a greater sense of commitment to the joint action. Moreover, the results show that participants’ sensitivity to the coordination manipulation was contingent on their prior attitudes towards the robot: participants in the High Coordination condition reported a greater sense of commitment than participants in the Low Coordination condition, except among those participants who were a priori least inclined to experience a close sense of relationship with the robot

Embodied language learning and cognitive bootstrapping: methods and design principles

Co-development of action, conceptualization and social interaction mutually scaffold and support each other within a virtuous feedback cycle in the development of human language in children. Within this framework, the purpose of this article is to bring together diverse but complementary accounts of research methods that jointly contribute to our understanding of cognitive development and in particular, language acquisition in robots. Thus, we include research pertaining to developmental robotics, cognitive science, psychology, linguistics and neuroscience, as well as practical computer science and engineering. The different studies are not at this stage all connected into a cohesive whole; rather, they are presented to illuminate the need for multiple different approaches that complement each other in the pursuit of understanding cognitive development in robots. Extensive experiments involving the humanoid robot iCub are reported, while human learning relevant to developmental robotics has also contributed useful results. Disparate approaches are brought together via common underlying design principles. Without claiming to model human language acquisition directly, we are nonetheless inspired by analogous development in humans and consequently, our investigations include the parallel co-development of action, conceptualization and social interaction. Though these different approaches need to ultimately be integrated into a coherent, unified body of knowledge, progress is currently also being made by pursuing individual methods

Optimal perceived timing: integrating sensory information with dynamically updated expectations

The environment has a temporal structure, and knowing when a stimulus will appear translates into increased perceptual performance. Here we investigated how the human brain exploits temporal regularity in stimulus sequences for perception. We find that the timing of stimuli that occasionally deviate from a regularly paced sequence is perceptually distorted. Stimuli presented earlier than expected are perceptually delayed, whereas stimuli presented on time and later than expected are perceptually accelerated. This result suggests that the brain regularizes slightly deviant stimuli with an asymmetry that leads to the perceptual acceleration of expected stimuli. We present a Bayesian model for the combination of dynamically-updated expectations, in the form of a priori probability of encountering future stimuli, with incoming sensory information. The asymmetries in the results are accounted for by the asymmetries in the distributions involved in the computational process

A user-centred framework for explainable artificial intelligence in human-robot interaction

State of the art Artificial Intelligence (AI) techniques have reached an impressive complexity. Consequently, researchers are discovering more and more methods to use them in real-world applications. However, the complexity of such systems requires the introduction of methods that make those transparent to the human user. The AI community is trying to overcome the problem by introducing the Explainable AI (XAI) field, which is tentative to make AI algorithms less opaque. However, in recent years, it became clearer that XAI is much more than a computer science problem: since it is about communication, XAI is also a Human-Agent Interaction problem. Moreover, AI came out of the laboratories to be used in real life. This implies the need for XAI solutions tailored to non-expert users. Hence, we propose a user-centred framework for XAI that focuses on its social-interactive aspect taking inspiration from cognitive and social sciences' theories and findings. The framework aims to provide a structure for interactive XAI solutions thought for non-expert users.Comment: Presented at AI-HRI symposium as part of AAAI-FSS 2021 (arXiv:2109.10836