robotics
A Robot Resolved an Underspecified Task by Looking Around
CLUE tested hypotheses in the environment instead of assuming the goal and map were complete.
Summary
CLUE tested hypotheses in the environment instead of assuming the goal and map were complete.
CLUE tackles natural-language tasks where a robot must infer both what success means and where relevant information might be. It forms task hypotheses, builds a language-embedded map online, tests possible plans through interaction and updates them as evidence arrives. On a Boston Dynamics Spot across 15 indoor and outdoor tasks, the authors report success within seven percentage points of an oracle and four times the rate of a planner without closed-loop feedback. The comparison covers three research environments and does not establish open-world reliability.
Why it matters
CLUE tested hypotheses in the environment instead of assuming the goal and map were complete.
Limits and context
- The comparison covers three research environments and does not establish open-world reliability.
Key claims
CLUE tested hypotheses in the environment instead of assuming the goal and map were complete.
Qualification: The comparison covers three research environments and does not establish open-world reliability.
Evidence: source-2026-09-28-007
Sources
- arXiv preprint 2609.30428arXiv · primary research
Corrections
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