  Controlling robots to perform tasks via natural language is one of the most
challenging topics in human-robot interaction. In this work, we present a robot
system that follows unconstrained language instructions to pick and place
arbitrary objects and effectively resolves ambiguities through dialogues. Our
approach infers objects and their relationships from input images and language
expressions and can place objects in accordance with the spatial relations
expressed by the user. Unlike previous approaches, we consider grounding not
only for the picking but also for the placement of everyday objects from
language. Specifically, by grounding objects and their spatial relations, we
allow specification of complex placement instructions, e.g. "place it behind
the middle red bowl". Our results obtained using a real-world PR2 robot
demonstrate the effectiveness of our method in understanding pick-and-place
language instructions and sequentially composing them to solve tabletop
manipulation tasks. Videos are available at
http://speechrobot.cs.uni-freiburg.de
