Manyquadrupeds: Learning a single locomotion policy for diverse quadruped robots
Learning a locomotion policy for quadruped robots has traditionally been constrained to a
specific robot morphology, mass, and size. The learning process must usually be repeated …
specific robot morphology, mass, and size. The learning process must usually be repeated …
Latent exploration for reinforcement learning
Abstract In Reinforcement Learning, agents learn policies by exploring and interacting with
the environment. Due to the curse of dimensionality, learning policies that map high …
the environment. Due to the curse of dimensionality, learning policies that map high …
MyoChallenge 2022: Learning contact-rich manipulation using a musculoskeletal hand
Manual dexterity has been considered one of the critical components for human evolution.
The ability to perform movements as simple as holding and rotating an object in the hand …
The ability to perform movements as simple as holding and rotating an object in the hand …
Hoisdf: Constraining 3d hand-object pose estimation with global signed distance fields
H Qi, C Zhao, M Salzmann, A Mathis - ar** items of many shapes
and qualities. Over millions of years, the musculoskeletal structure, central and peripheral …
and qualities. Over millions of years, the musculoskeletal structure, central and peripheral …
[PDF][PDF] Human Motion Simulation Using Reinforcement Learning
J Adriaens - 2023 - matheo.uliege.be
The simulation of realistic human motion is a critical aspect in several fields. Ranging from
character animations in video games to medical research, human motion simulation is …
character animations in video games to medical research, human motion simulation is …