DSRL-DCT RL Achieves 100% Success in Mobile Manipulation
rohanpaul_ai · x · 2026-07-05
DSRL-DCT is the reinforcement learning component of the framework, which the company claims achieves a 100% success rate on mobile manipulation tasks. It freezes a pre-trained VLA model and learns only a smaller noise selection policy, using Discrete Cosine Transform (DCT) to compress the robot's massive action space into a smaller latent space.
More from Embodied
- Teachers decry plan to put a humanoid robot in a New York high school — nordicinst · 2026-07-27
- NUS builds a soft force sensor that drives actuators without electronics or power — CurieuxExplorer · 2026-07-27
- Chelsea Finn says robot RL is bottlenecked by physical rollout cost, not algorithms — ycombinator · 2026-07-27
- Robot goes to the fridge and fetches a beer — Darpinian · 2026-07-27
- Researchers show digital circuits can be replicated with knitted fabric — mtizard · 2026-07-27
- Local Qwen models power a robot that tests 78 smartphones’ battery life — gappyvalley · 2026-07-27