This paper presents the RL framework for walking of a 6DOF planar bipedal robot with a prismatic knee joint. The prismatic knee joint allows the robot to adapt to varying terrain and maintain ...

This project demonstrates the implementation of a policy-gradient-based method called REINFORCE from scratch, a fundamental Deep Reinforcement Learning (DRL) algorithm. The primary goal is to train a ...

While Boston Dynamics and dancing robots usually receive most of the attention, there are some major developments taking place behind the scenes that don’t receive enough coverage. One of those ...

Figure is one of several startups chasing the sci-fi-driven vision of general-purpose, humanoid robots, with domestic competitors like Tesla's Optimus, and Agility Robotics' Digital also pushing ...

For example, a pair of robot legs called Cassie taught itself to walk using reinforcement learning, but only after it had done so in a simulation. “The problem is your simulator will never be as ...

Virtual limitations: Reinforcement learning has been used to train many bots to walk inside simulations, but transferring that ability to the real world is hard. “Many of the videos that you see ...

Creating a reinforcement learning (RL) model for an autopilot system using Python and X-Plane requires integrating X-Plane's simulation environment with a reinforcement learning framework. Below is an ...

Watch: Mini Chinese bipedal robot tackles obstacles with precision using AI models. Mini π uses control algorithms like ZMP, WPC+MPC, and reinforcement learning, with ROS for navigation and ...

Using reinforcement learning, they were able to achieve a new top-speed for the robot of 3.9m/s, or roughly 8.7mph. You can watch what that looks like in the video below: ...