Reproduce “H-SAUR: Hypothesize, Simulate, Act, Update, and Repeat for Understanding Object Articulations from Interactions” on OpenResearch
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About this paper
Kei Ota, Hsiao-Yu Tung, Kevin A. Smith, Anoop Cherian, Tim K. Marks, Alan Sullivan, Asako Kanezaki, Joshua B. Tenenbaum
H-SAUR lets a robot infer how an unfamiliar articulated object moves and plan actions. It simulates candidate mechanisms, tests actions on the object, compares observed motion with predictions, and updates its hypotheses; for blocked goals, it addresses obstructing parts in sequence. In simulated PuzzleBoxes, it succeeds in 80.0% of three-chain attempts, versus 0.0% for three baselines; this is limited to tested tasks.
Summary by alphaXiv.
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