Robotics

Generalized State-Dependent Exploration for Deep Reinforcement Learning in Robotics

We extend the original state-dependent exploration (SDE) to apply deep reinforcement learning algorithms directly on real robots. The resulting method, gSDE, yields competitive results in simulation but outperforms the unstructured exploration on the real robot.

Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics

We evaluate the benefits of decoupling feature extraction from policy learning in robotics and propose a new way of combining state representation learning methods.

Learning to Drive Smoothly in Minutes

Learning to drive smoothly in minutes using reinforcement learning on a Donkey Car.

Learning to Drive Smoothly in Minutes

Learning to drive smoothly in minutes using reinforcement learning on a Donkey Car.

S-RL Toolbox

S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics

S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning

State representation learning aims at learning compact representations from raw observations in robotics and control applications. Approaches used for this objective are auto-encoders, learning forward models, inverse dynamics or learning using …

PythonRobotics: a Python code collection of robotics algorithms

This is a Python code collection of robotics algorithms, especially for autonomous navigation.

Simple and Robust {Computer — Arduino} Serial Communication

Arduino built-in functions for sending/receiving data are not very handy and sturdy. We introduce a protocol to communicate (using serial port, bluetooth or sockets) with the Arduino (but not only) in a simple and robust way.

Autonomous Racing Robot With an Arduino, a Raspberry Pi and a Pi Camera

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Racing Robot

Autonomous Racing Robot With an Arduino, a Raspberry Pi and a Pi Camera