arXiv subjects

Ricardo Sanz

Publications and source records attributed to Ricardo Sanz.

5 recordsLinked to original sources

arXiv2025

Robot Metacognition: Decision Making with Confidence for Tool Invention

Robots today often miss a key ingredient of truly intelligent behavior: the ability to reflect on their own cognitive processes and decisions. In humans, this self-monitoring or metacognition is crucial for learning, decision making and problem solving. For instance, they can evaluate how confident they are in performing a task, thus regulating their own behavior and allocating proper resources. Taking inspiration from neuroscience, we propose a robot metacognition architecture centered on confidence (a second-order judgment on decisions) and we demonstrate it on the use case of autonomous tool invention. We propose the use of confidence as a metacognitive measure within the robot decision making scheme. Confidence-informed robots can evaluate the reliability of their decisions, improving their robustness during real-world physical deployment. This form of robotic metacognition emphasizes embodied action monitoring as a means to achieve better informed decisions. We also highlight potential applications and research directions for robot metacognition.

cs.RO↗

arXiv2025

In silico evaluation of pramlintide dosing algorithms in artificial pancreas systems

Pramlintide's capability to delay gastric emptying has motivated its use in artificial pancreas systems, accompanying insulin as a control action. Due to the scarcity of pramlintide simulation models in the literature, in silico testing of insulin-plus-pramlintide strategies is not widely used. This work incorporates a recent pramlintide pharmacokinetics/pharmacodynamics model into the T1DM UVA/Padova simulator to adjust and validate four insulin-plus-pramlintide control algorithms. The proposals are based on an existing insulin controller and administer pramlintide either as independent boluses or as a ratio of the insulin infusion. The results of the insulin-pramlintide algorithms are compared against their insulin-alone counterparts, showing an improvement in the time in range between 3.00\% and 10.53\%, consistent with results reported in clinical trials in the literature. Future work will focus on individualizing the pramlintide model to the patients' characteristics and evaluating the implemented strategies under more challenging scenarios.

eess.SY↗

arXiv2024

Awareness in robotics: An early perspective from the viewpoint of the EIC Pathfinder Challenge "Awareness Inside''

Consciousness has been historically a heavily debated topic in engineering, science, and philosophy. On the contrary, awareness had less success in raising the interest of scholars in the past. However, things are changing as more and more researchers are getting interested in answering questions concerning what awareness is and how it can be artificially generated. The landscape is rapidly evolving, with multiple voices and interpretations of the concept being conceived and techniques being developed. The goal of this paper is to summarize and discuss the ones among these voices connected with projects funded by the EIC Pathfinder Challenge called ``Awareness Inside'', a nonrecurring call for proposals within Horizon Europe designed specifically for fostering research on natural and synthetic awareness. In this perspective, we dedicate special attention to challenges and promises of applying synthetic awareness in robotics, as the development of mature techniques in this new field is expected to have a special impact on generating more capable and trustworthy embodied systems.

cs.RO↗

arXiv2024

The landscape of Collective Awareness in multi-robot systems

The development of collective-aware multi-robot systems is crucial for enhancing the efficiency and robustness of robotic applications in multiple fields. These systems enable collaboration, coordination, and resource sharing among robots, leading to improved scalability, adaptability to dynamic environments, and increased overall system robustness. In this work, we want to provide a brief overview of this research topic and identify open challenges.

cs.RO↗

arXiv2023

Category Theory for Autonomous Robots: The Marathon 2 Use Case

Model-based systems engineering (MBSE) is a methodology that exploits system representation during the entire system life-cycle. The use of formal models has gained momentum in robotics engineering over the past few years. Models play a crucial role in robot design; they serve as the basis for achieving holistic properties, such as functional reliability or adaptive resilience, and facilitate the automated production of modules. We propose the use of formal conceptualizations beyond the engineering phase, providing accurate models that can be leveraged at runtime. This paper explores the use of Category Theory, a mathematical framework for describing abstractions, as a formal language to produce such robot models. To showcase its practical application, we present a concrete example based on the Marathon 2 experiment. Here, we illustrate the potential of formalizing systems -- including their recovery mechanisms -- which allows engineers to design more trustworthy autonomous robots. This, in turn, enhances their dependability and performance.

cs.RO↗