
Sankaet
@sankaet • 13,352 subscribers
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This is a 20-minute unedited on/off-gantry run from today. What's special about it is that no gains were tuned on the robot before we started running the policy. This is the DVBF-based motion policy we've been working on, which is turning out to be quite special. The goal of using DVBF is to ensure policies can be deployed on many robots at once without manual gain adjustment before the policy runs reliably on each robot.
Sankaet36,570 次观看 • 7 个月前

Like LLMs, autoregressive transformers for action tokens need a reasoning layer to reduce hallucinations and boost reliability. Grounding this layer in the physics of the action space using DVBFs makes for scalable, task-agnostic training—far simpler than creating RL reward functions for each task. Learn more about our novel approach in the video below 👇🏼
Sankaet52,565 次观看 • 1 年前
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