Reproduce “Kinematic Hypothesis Context: Embodiment-Conditioned Learned Video Coding for Bandwidth-Limited Robot Policy Uplinks” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Yuze Lu
The authors introduce kinematic hypothesis context (KHC), which uses robot states, geometry, and camera calibration to warp a decoded image into candidate current views that condition video compression. It also lets skipped frames display a current-pose hypothesis. At 6 kbps, KHC-skip achieves 43.1% task success versus 22.8% for a history-only codec; this result depends on synchronized states and calibrated cameras.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.