This paper is focused on solving the multiple robots motion planning problem in a robust way, whereas we say that a motion plan is robust if it can be used in spite of small variations in the motion context. After a critical review of our previous research on generating multiple robots motion plans, we classify several ''sources of instability'' useful for establishing criteria for robustness. These sources include variations of the environment model, variations in the number of robots and paths, and variations in the motion parameters of the moving items. We define various ''Impact Factors''. that evaluate how much a variation affects a given plan. For example, a new path (for a robot) can be associated with a Collision Impact Factor, that estimate how many collisions among moving objects may occur along that path. Hence, to evaluate the motion plan robustness, we define how quality values for motion plans are modified by the Impact Factors.
A framework for robust multiple robots motion planning
FERRARI, CARLO;PAGELLO, ENRICO;
1996
Abstract
This paper is focused on solving the multiple robots motion planning problem in a robust way, whereas we say that a motion plan is robust if it can be used in spite of small variations in the motion context. After a critical review of our previous research on generating multiple robots motion plans, we classify several ''sources of instability'' useful for establishing criteria for robustness. These sources include variations of the environment model, variations in the number of robots and paths, and variations in the motion parameters of the moving items. We define various ''Impact Factors''. that evaluate how much a variation affects a given plan. For example, a new path (for a robot) can be associated with a Collision Impact Factor, that estimate how many collisions among moving objects may occur along that path. Hence, to evaluate the motion plan robustness, we define how quality values for motion plans are modified by the Impact Factors.Pubblicazioni consigliate
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