Author: Gabriel Giangi
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Part 3: Building the Hexapod Simulation Environment
In this third instalment of the intelligent hexapod series, I explored the integration of the physical robot into a simulation environment using ROS2 (Robot Operating System 2). I provided clear instructions on the setup process, focusing on ROS2 concepts such as nodes, topics, and messages that facilitate efficient communication between components. Additionally, I discussed the…
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Part 2: Assembly and Electronics – Bringing the Hexapod to Life
In this second part of my blog series on building an intelligent hexapod robot, I delve into the assembly process and the electronics embedded within the system. Discover how I integrated servo motors, the Raspberry Pi Pico RP2040 board, and various sensors to bring the hexapod to life. Despite encountering a few challenges along the…
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Part 1: Hexapod – Exploring the Intersection of Hardware and Intelligence
Embark on a captivating journey with me as we delve into the world of Hexapods, exploring the fascinating fusion of hardware and intelligence. Join my research endeavor as we unravel the crucial role of embedded systems and intelligent hardware in realizing true artificial general intelligence. From 3D modeling to post-processing and painting, witness the meticulous…
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Towards AGI in Robotics: An Exploratory Approach to Self-Maintenance
Building upon the quest for General Artificial Intelligence (AI) in robotics, this article proposes a novel architecture for a self-maintaining robot. Employing a triad of Perception, Cognition, and Action modules, the approach leverages machine learning techniques, reinforcement learning, and control theory, allowing the robot to monitor and manage its energy consumption, troubleshoot faults, and perform…
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Federated Graph Neural Networks: An In-Depth Look
In the evolving field of Federated Learning, an under-explored aspect lies in the relationships between participants, often forming a complex graph topology. This post delves into the concept of these relationship graphs, using medical research collaboration and import/export logistic tracking as real-world examples.
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SPEAR
Leveraging a vast dataset and a state-of-the-art deep learning approach, SPEAR delivers unmatched SER performance.
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Harnessing the Power of Affective Computing: Use Cases and Research Areas
In the intriguing field of affective computing, Speech Emotion Recognition (SER) stands out as a rapidly evolving discipline. With the advent of deep learning and large pre-trained self-supervised models like Wav2Vec 2.0 and WavLM, SER is undergoing a significant transformation. The introduction of the SEIR-DB, one of the most diverse SER datasets, and the development…
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SEIR-DB
The Speech Emotion Intensity Recognition Database aims to facilitate tasks related to speech emotion recognition.
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DispatchBoost
DispatchBoost is an advanced system designed to optimize routing decisions for efficient and cost-effective transportation.
Gabriel Giangi 