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

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.

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 ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Amazon today launched SageMaker Reinforcement Learning (RL) Kubeflow ...

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...

Over the past two decades, humanoid robots have greatly improved their ability to perform functions like grasping objects and using computer vision to detect things since Honda’s release of the ASIMO ...

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 field of robotics, a classic application of artificial intelligence, has recently been amplified by the very new and fashionable technology of generative AI, programs such as large language models ...