We have 3 of 195 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Mastering robot manipulation skills via reinforcement learning (RL) remains largely sample-inefficient. The most common RL algorithms rely on random action sampling to discover new strategies, resulting in agents that allocate most of their training budget to motions in free space, away from the contacts from which man...
Time-Adaptive Robotic Control (TARC), a reinforcement learning framework in which the policy jointly predicts a control action and its duration of application, is introduced, and matches the performance of high-frequency discrete-time controllers while operating at less than half their control frequency.
An automatic human-to-quadruped puppeteering framework that produces plausible and controllable quadruped motions from ordinary human motion data and enables fine-grained intuitive control of the quadruped motion such as head movement control and individual limb puppeteering.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
