Abstract
For the past several years research on robot problem-solving methods has centered on what may one day be called “simple” plans: linear sequences of actions to be performed by single robots to achieve single goals in static environments. Recent speculation and preliminary work at several research centers has suggested a variety of ways in which these traditional constraints could be relaxed. In this paper we describe some of the possible extensions, illustrating the discussion where possible with examples taken from the current Stanford Research Institute robot system.
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