Control-Driven Mapping and Planning
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Abstract
Layered hybrid controllers typically include a
planner at the top level with reactive control at the lower
levels. The planner considers the state of the robot in a
global context. The low-level controllers consider only the local environment of the robot and are able to operate at a high frequency to ensure the safety of the robot. Also, it is often the case that the low-level controllers consider more aspects of
the robot's state (e.g. kinematic constraints) than the planner.
The consideration of such constraints at the planning level
would prohibitively increase the state space the planner must
consider and, accordingly, its running time and complexity. In
this paper, we investigate how we can take advantage at the
planning level of domain knowledge encapsulated in the lower
level controllers, and we introduce a feedback mechanism that
enables low-level controllers to influence the high-level planner.
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2007-11
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