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Pick-and-place is one of the fundamental tasks in robotics research. However,the attention has been mostly focused on the ``pick'' task, leaving the``place'' task relatively unexplored. In this paper, we address the problem ofplacing objects in the context of a teleoperation framework. Particularly, wefocus on two aspects of the place task: stability robustness and contextualreasonableness of object placements. Our proposed method combinessimulation-driven physical stability verification via real-to-sim and thesemantic reasoning capability of large language models. In other words, givenplace context information (e.g., user preferences, object to place, and currentscene information), our proposed method outputs a probability distribution overthe possible placement candidates, considering the robustness andreasonableness of the place task. Our proposed method is extensively evaluatedin two simulation and one real world environments and we show that our methodcan greatly increase the physical plausibility of the placement as well ascontextual soundness while considering user preferences.

SPOTS: Stable Placement of Objects with Reasoning in Semi-Autonomous Teleoperation Systems