This multi-objective setup encourages natural walking behavior rather than rigid or inefficient movement. A four-stage ...

A quadruped robot uses deep reinforcement learning to master walking on varied terrains, demonstrating energy-efficient and ...

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 ...

AI can help develop methods of locomotion that are unconventional but fast AI can help develop methods of locomotion that are unconventional but fast is a senior reporter who has covered AI, robotics, ...

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

[Aditya Sripada] and [Abhishek Warrier]’s TARS3D robot came from asking what it would take to make a robot with the capabilities of TARS, the robotic character from Interstellar. We couldn’t find a ...

Boasting a sophisticated design tailored for versatile mobility, Cassie demonstrates remarkable agility as it effortlessly navigates quarter-mile runs and performs impressive long jumps without ...

The companies have jointly developed an AI robot control system that can interact with the physical world and be used in various fields from logistics to rescue operations. Tests have shown that in ...