Chapter 10 - Motion Planning
Published online by Cambridge University Press: 05 June 2014
Summary
This section describes the methods used to implement the deliberative autonomy layer that was initially described in Chapter 1. Planning concerns the question of deciding what to do, of which deciding where to go is a special case. Central to planning is the predictive model, which maps candidate actions onto their associated consequences. Equally as important is the mechanism of search because there tend to be many alternative actions to be assessed at any point in time.
Planners think about the future, employing some degree of look ahead and there is a central trade-off between the computational cost of look ahead and the cognitive performance of the system. In addition to perception, planning is where most of what impresses us about robots is located. Given a sufficiently accurate model of the environment, planning technology today can solve, in a comparative instant, problems that we humans would find quite daunting.
Introduction
Planning refers to processes that deliberate, predict, and often optimize. Respectively these actions will mean:
Deliberate: Consider many possible sequences of future actions.
Predict: Predict the outcomes for each sequence.
Optimize: Pick one, perhaps based on some sense of relative merit.
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- Information
- Mobile RoboticsMathematics, Models, and Methods, pp. 640 - 690Publisher: Cambridge University PressPrint publication year: 2013