Gradient-based Planning for World Models at Longer Horizons

<!-- twitter --> <div style="display: flex; margin-bottom: 1.5em;"> <img alt="BallNav demo" src="https://bair.berkeley.edu/static/blog/grasp/ballnav_demo.gif" /> <img alt="Push-T demo" src="https://bair.berkeley.edu/static/blog/grasp/pusht_zoomout.gif" /> </div> <p><strong>GRASP</strong> is a new gradient-based planner for learned dynamics (a “world model”) that makes long-horizon planning practical by (1) lifting the trajectory into virtual states so optimization is parallel