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Use of physics-based simulation as a planning model enables a planner toreason and generate plans that involve non-trivial interactions with the world.For example, grasping a milk container out of a cluttered refrigerator mayinvolve moving a robot manipulator in between other objects, pushing away theones that are movable and avoiding interactions with certain fragilecontainers. A physics-based simulator allows a planner to reason about theeffects of interactions with these objects and to generate a plan that graspsthe milk container successfully. The use of physics-based simulation forplanning however is underutilized. One of the reasons for it being thatphysics-based simulations are typically way too slow for being used within aplanning loop that typically requires tens of thousands of actions to beevaluated within a matter of a second or two. In this work, we develop aplanning algorithm that tries to address this challenge. In particular, itbuilds on the observation that only a small number of actions actually need tobe simulated using physics, and the remaining set of actions, such as moving anarm around obstacles, can be evaluated using a much simpler internal planningmodel, e.g., a simple collision-checking model. Motivated by this, we developan algorithm called Planning with Selective Physics-based Simulation thatautomatically discovers what should be simulated with physics and what canutilize an internal planning model for pick-and-place tasks.

Planning with Selective Physics-based Simulation for Manipulation Among Movable Objects