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Nowadays robotic systems are expected to share workspaces and collaborate with humans. In such collaborative environments, an important challenge is to ground or establish the correct semantic interpretation of a human request. Once such an interpretation is available, the request must be translated into robot motion commands in order to complete the desired task. It is not unusual that a human request cannot be grounded to a unique interpretation, thus leading to an ambiguous request. A simple example is to ask a robot to &#x201C;put a cup on the table,&#x201D; when there are multiple cups available. In order to deal with this kind of ambiguous request, we propose a delayed or lazy variable grounding. The focus of this paper is a motion planning algorithm that, given goal regions that represent different valid groundings, lazily finds a feasible path to any one valid grounding. This algorithm includes a reward-penalty strategy, which attempts to prioritize those goal regions that seem more promising to provide a solution. We validate our approach by solving requests with multiple valid alternatives in both simulation and real-world experiments.

Lazy Evaluation of Goal Specifications Guided by Motion Planning