154 research outputs found
Lo spirito di fronte al male. L'ultima filosofia di Giovanni Gentile
No full textThe essay retraces Giovanni Gentile’s philosophical production
from 1943 until his death in 1944, 15 April. Focusing
on Genesi e struttura della società, the author investigates the
most signifi cant theoretical differences between this last book
(published in 1946, after Gentile’s death) and the philosophical
works written twenty years before, Fondamenti di Filosofi a
del diritto and Teoria generale dello spirito come atto puro. The
author points out concepts such as evil and death in these
books and studies their different elaboration in Gentile’s last
book, considering a possible link between these changes and
the anxiety or moral suffering that the philosopher might have
felt facing the Nazi Fascist crimes
Position-Agnostic Autonomous Navigation in Vineyards with Deep Reinforcement Learning
No full textPrecision agriculture is rapidly attracting research to efficiently introduce
automation and robotics solutions to support agricultural activities. Robotic
navigation in vineyards and orchards offers competitive advantages in
autonomously monitoring and easily accessing crops for harvesting, spraying and
performing time-consuming necessary tasks. Nowadays, autonomous navigation
algorithms exploit expensive sensors which also require heavy computational
cost for data processing. Nonetheless, vineyard rows represent a challenging
outdoor scenario where GPS and Visual Odometry techniques often struggle to
provide reliable positioning information. In this work, we combine Edge AI with
Deep Reinforcement Learning to propose a cutting-edge lightweight solution to
tackle the problem of autonomous vineyard navigation without exploiting precise
localization data and overcoming task-tailored algorithms with a flexible
learning-based approach. We train an end-to-end sensorimotor agent which
directly maps noisy depth images and position-agnostic robot state information
to velocity commands and guides the robot to the end of a row, continuously
adjusting its heading for a collision-free central trajectory. Our extensive
experimentation in realistic simulated vineyards demonstrates the effectiveness
of our solution and the generalization capabilities of our agent
Waypoint Generation in Row-Based Crops with Deep Learning and Contrastive Clustering
No full textThe development of precision agriculture has gradually introduced automation in the agricultural process to support and rationalize all the activities related to field management. In particular, service robotics plays a predominant role in this evolution by deploying autonomous agents able to navigate in fields while executing different tasks without the need for human intervention, such as monitoring, spraying and harvesting. In this context, global path planning is the first necessary step for every robotic mission and ensures that the navigation is performed efficiently and with complete field coverage. In this paper, we propose a learning-based approach to tackle waypoint generation for planning a navigation path for row-based crops, starting from a top-view map of the region-of-interest. We present a novel methodology for waypoint clustering based on a contrastive loss, able to project the points to a separable latent space. The proposed deep neural network can simultaneously predict the waypoint position and cluster assignment with two specialized heads in a single forward pass. The extensive experimentation on simulated and real-world images demonstrates that the proposed approach effectively solves the waypoint generation problem for both straight and curved row-based crops, overcoming the limitations of previous state-of-the-art methodologies
Deep Semantic Segmentation at the Edge for Autonomous Navigation in Vineyard Rows
No full textPrecision agriculture is a fast-growing field that aims at introducing affordable and effective automation into agricultural processes. Nowadays, algorithmic solutions for navigation in vineyards require expensive sensors and high computational workloads that preclude large-scale applicability of autonomous robotic platforms in real business case scenarios. From this perspective, our novel proposed control leverages the latest advancement in machine perception and edge AI techniques to achieve highly affordable and reliable navigation inside vineyard rows with low computational and power consumption. Indeed, using a custom-trained segmentation network and a low-range RGB-D camera, we are able to take advantage of the semantic information of the environment to produce smooth trajectories and stable control in different vineyards scenarios. Moreover, the segmentation maps generated by the control algorithm itself could be directly exploited as filters for a vegetative assessment of the crop status. Extensive experimentations and evaluations against real-world data and simulated environments demonstrated the effectiveness and intrinsic robustness of our methodology
An Adaptive Row Crops Path Generator with Deep Learning Synergy
No full textThe autonomous navigation of agricultural field machines strongly depends on the global path generation system. Indeed, a correct and effective path construction heavily influences the overall navigation stack compromising the successfulness of the robot mission. However, the most commonly used search algorithms struggle to adapt to environments where a significant prior knowledge of the domain is not negligible. Despite this crucial factor, path generation for row-based crops has received little attention from the research community so far. The proposed research introduces a novel global path planning system that works in synergy with a deep learning model to provide an accurate and centered path with respect to the rows of the analyzed crop. It guarantees the full coverage of the given occupancy grid with less processing time compared to other available literature solutions. Moreover, the presented methodology can detect an anomaly in the path generation and provide the hypothetical user feedback of the missing full coverage of the given crop. Indeed, especially in a practical application, the correct coverage and centrality of the path are essential for effective autonomous navigation. Experimentation with synthetic and real-world satellite occupancy grid maps clearly show the advantages of the proposed methodology and its intrinsic robustness
Il silenzio dell’atto puro. Giovanni Gentile e la questione morale
No full textThe essay retraces Giovanni Gentile’s theoretical and political production from 1943 until his death on the 15th april 1944. The author investigates the reasons that led the philosopher to engage with the Italian Social Republic and underlines how Gentile, in his writings and speeches, always calls for national peace, in order to defend the country’s unity despite the ongoing war. Once Gentile’s political position is reconstructed, the second part of the paper deals with the most significant theoretical changes regarding the philosopher’s last volume Genesi e struttura della società. Then, the author considers a possible link between the anxiety or moral suffering that the philosopher might have felt facing the Nazi Fascist crimes and some pages of the volume in which there is a reflection on the conflictual nature of the social being and on the problem of death
A Deep Learning Driven Algorithmic Pipeline for Autonomous Navigation in Row-Based Crops
No full textExpensive sensors and inefficient algorithmic pipelines significantly affect the overall cost of autonomous machines. However, affordable robotic solutions are essential to practical usage, and their financial impact constitutes a fundamental requirement for employing service robotics in most fields of application. Among all, researchers in the precision agriculture domain strive to devise robust and cost-effective autonomous platforms in order to provide genuinely large-scale competitive solutions. In this article, we present a complete algorithmic pipeline for row-based crops autonomous navigation, specifically designed to cope with low-range sensors and seasonal variations. Firstly, we build on a robust data-driven methodology to generate a viable path for the autonomous machine, covering the full extension of the crop with only the occupancy grid map information of the field. Moreover, our solution leverages on latest advancement of deep learning optimization techniques and synthetic generation of data to provide an affordable solution that efficiently tackles the well-known Global Navigation Satellite System unreliability and degradation due to vegetation growing inside rows. Extensive experimentation and simulations against computer-generated environments and real-world crops demonstrated the robustness and intrinsic generalizability to different factors of variations of our methodology that open the possibility of highly affordable and fully autonomous machines
PIC4rl-gym: a ROS2 modular framework for Robots Autonomous Navigation with Deep Reinforcement Learning
No full textLearning agents can optimize standard autonomous navigation improving
flexibility, efficiency, and computational cost of the system by adopting a
wide variety of approaches. This work introduces the \textit{PIC4rl-gym}, a
fundamental modular framework to enhance navigation and learning research by
mixing ROS2 and Gazebo, the standard tools of the robotics community, with Deep
Reinforcement Learning (DRL). The paper describes the whole structure of the
PIC4rl-gym, which fully integrates DRL agent's training and testing in several
indoor and outdoor navigation scenarios and tasks. A modular approach is
adopted to easily customize the simulation by selecting new platforms, sensors,
or models. We demonstrate the potential of our novel gym by benchmarking the
resulting policies, trained for different navigation tasks, with a complete set
of metrics
Espressione e vita. Lo Spinoza di Gilles Deleuze
No full textThe essay considers Gilles Deleuze’s writings on Spinoza (Spinoza and the Problem of Expression and Spinoza. Practical Philosophy) and both the elements of continuity among the different Deleuzian readings of Spinoza and the specific differences of each work are highlighted. It will be observed how in the two works there is a strong attention towards the Spinozian concepts of immanence and univocity. However, if the first one has a certain structuralist setting out in the reading of Deleuze, this characteristics seems to weaken progressively, in favor of an understanding of Spinoza’s thought as a practical philosophy and ethics that is primarily open to the experience of singularity. The Deleuzian interpretation of Spinoza is reconstructed in its internal logics, but also on the background of the French philosophical historiography on the author, that is coeval to Deleuze’s volumes
Paura. Forme della percezione e strategie di governo ne "Les Passions de l’âme" e nell’ "Ethica"
No full textFear. Form of Perception and Government Strategies in Les Passions de l’ âme and in Ethica
My paper focuses on the analysis of the terms «dread» and «fear» both in The Passions of
the Soul, where Descartes respectively indicates them as Crainte and Peur, and in Spinoza’s
Ethics, where the author uses the words timor and metus. First of all, I underline the characteristics,
the relevance and the usefulness of these affections, together with the strategies of
control used to prevent their transformation into passions that inhibit rational action. I will
then expose the divergence of views in Descartes and Spinoza pertaining the delineation of
these affective conditions, as well as, in the second part of my paper, I focus on the analogies
concerning the rational strategies the human being can assume in order to handle dread and
fear. Besides Descartes e Spinoza, it is necessary to recall Hobbes’s Leviathan, since this
work is a consistent and relevant source for Spinoza, as far as the conception of fear as a peculiar
perception of past and present is concerned
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