Deep dives into Robotics, Artificial Intelligence, and C++ programming. Join me on a journey of continuous learning and innovation.
A deep dive into Physical Intelligence's π*0.6 model and the RECAP method - an elegant technique that enables Vision-Language-Action models to improve through reinforcement learning without requiring policy gradients.
Exploring the next frontier in robotics, where intelligent, adaptable machines transform our lives through flexibility, autonomy, and the fusion of AI with physicality.
Discover a robust three-step algorithm for generating vehicle speed profiles that guarantees adherence to physical constraints while remaining computationally efficient. Perfect for robotics and autonomous systems!
An in-depth exploration of Physical Intelligence in robotics, focusing on the integration of AI with physical interaction and adaptability.
Learn how to train a quadruped robot to walk using reinforcement learning, from defining actions and observations to designing rewards and transitioning from simulation to reality.
A comprehensive guide to footstep planning for bipeds and quadrupeds, covering 2D and 3D foot trajectories, ZMP generation, and CoM trajectory computation.
Learn how to build a wake-word detection system for your devices, exploiting NLP and AI. Understand the key concepts, training process and its application in robotics.
Learn how flow matching generates continuous data, such as robot actions, by denoising samples drawn from a simple noise distribution. Understand the key concepts, training process, and application in robotics.
A comprehensive guide to understanding and implementing Graph SLAM, covering theoretical foundations, mathematical principles, and practical implementation with real-world examples.
A deep dive into Quadratic Programming, covering theory, applications, and solution methods with practical examples.
An exploration of line search methods for solving unconstrained optimization problems, including their implementation and convergence properties.
A comprehensive guide to seamlessly integrating custom C++ libraries with ROS 2 for enhanced robot capabilities.
Exploring my experience with Dynamis PRC in Formula Student, including the exciting world of autonomous racing.
Exploring the exciting world of autonomous racing through PoliMove's participation in A2RL and the advancements in autonomous vehicle technology.
Exploring an optimal control system using Model Predictive Control for autonomous vehicle navigation in dynamic traffic.
A comprehensive guide to writing effective unit tests for robotic software components, with practical examples and best practices in C++.
Dive deep into the world of concurrent programming in C++ for robotics. Explore threading, synchronization techniques, and strategies for creating efficient multi-threaded robotic systems. Learn how to leverage mutexes, condition variables, and atomic operations to build responsive and robust robots.
Explore the intricacies of memory management in C++ with a focus on robotics applications. Learn about RAII, smart pointers, and best practices to write efficient and robust code while avoiding common memory-related pitfalls.
Explore key features introduced in C++17 and C++20 that are particularly relevant for robotics development. Learn about structured bindings, concepts, ranges, coroutines, and more to enhance your C++ coding in robotics projects.
An overview of the autonomous driving modules in the Dynamis PRC Formula Student car.
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