Reinforcement learning (RL) is a branch of machine learning that enables robots to learn from their own actions and rewards, without requiring explicit supervision or predefined rules. RL can be ...

Algorithms such as decision trees, neural networks, or reinforcement learning can be used to build the model. The trained model is then deployed into the robot, which starts interacting with students.

When we think about machine learning, our minds often jump to datacenters full of sweating, overheating GPUs. However, lighter-weight hardware can also be used to these ends, as demonstrated by [Ni… ...

The creator manually controlled the robot while collecting LIDAR measurements and control labels, amassing valuable data for training. The subsequent machine learning phase involved feature selection, ...

In this project, we have designed a simple Hand Gesture Controlled Robot using Arduino. This Hand Gesture Controlled Robot is based on Arduino Nano, MPU6050, RF Transmitter-Receiver Pair and L293D ...

His current interest is reinforcement learning on a tiny scale. He came down to the 2023 Hackaday Supercon to tell us all about his work. Continue reading “Supercon 2023: Teaching Robots How To ...

Reinforcement learning techniques could be the keys to integrating robots — who use machine learning to output more than words — into the real world.

The Robotics and AI (RAI) Institute has developed the Ultra Mobility Vehicle (UMV), a self-balancing robotic bike capable of navigating challenging terrain and even jumping onto high surfaces.

A team has shown that reinforcement learning -i.e., a neural network that learns the best action to perform at each moment based on a series of rewards- allows autonomous vehicles and underwater ...

NVIDIA's new AI model trains robots to move like LeBron and Ronaldo Meta's $33 billion loser now looks like a winner Casetify were a little too inspired by Dbrand's X-ray skins and now it's ...