Using Monocular SLAM + Ego Video to Build Usable RL Environments for Embodied AI
chris_j_paxton · x · 2026-09-11
chrisjpaxton highlights an approach that combines monocular SLAM with egocentric video to create usable reinforcement learning environments for embodied AI, potentially cutting the cost of building training environments without real robots or hand-crafted simulation assets.
More from Embodied
- GPT-6 Astra drives a robot arm on first try via physical ICL; Ken Goldberg touts Agentic Robotics — zhaoran_wang · 2026-09-11
- Rabbit pushes surprise OTA update fixing R1 battery drain and SIM connectivity — SimonBalmain · 2026-09-11
- Masked Mimic now playable on Miniverse with sparse point control mode — carlosdponx · 2026-09-11
- Shanghai team open-sources running, jumping DIY humanoid robot with full hardware and RL training stack — tom_doerr · 2026-09-11
- mjbatch is now on PyPI: install with one pip command — kevin_zakka · 2026-09-11
- ego2wrist: Faking robot wrist-camera views from egocentric video, then testing if they work — chris_j_paxton · 2026-09-11