SOURCE-LINKED INTELLIGENCE

Imagine-TAMP: Imagination-Guided Task and Motion Planning in Partial Observability

arXiv · AI, language, vision and robotics · article · Sep 17, 2026 · UTC

Robots operating in cluttered environments must often manipulate objects whose locations are only partially observable. A central challenge is deciding whether to acquire another observation or to first manipulate objects that may occlude the target. Conventional task and motion planning (TAMP) approaches typically make this decision using symbolic action costs or expensive geometric planning, neither of which adequately captures how likely an observation is to reveal an occluded target. We introduce Imagine-TAMP, an interleaved planning and execution framework that uses semantic and geometric

Read original source ↗ Open in workspace

recordType

paper

region

Global