Multi-goal planning for an autonomous blasthole drill

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Abstract

This paper presents multi-goal planning for an autonomous blasthole drill used in open pit mining operations. Given a blasthole pattern to be drilled and constraints on the vehicle's motion and orientation when drilling, we wish to compute the best order in which to drill the given pattern. Blasthole pattern drilling is an asymmetric Traveling Salesman Problem with precedence constraints specifying that some holes must be drilled before others. We wish to find the minimum cost tour according to criteria that minimize the distance travelled satisfying the precedence and vehicle motion constraints. We present an iterative method for solving the blasthole sequencing problem using the combination of a Genetic Algorithm and motion planning simulations that we use to determine the true cost of travel between any two holes. Copyright © 2009, Association for the Advancement of Artificial Intelligence. All rights reserved.

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APA

Elinas, P. (2009). Multi-goal planning for an autonomous blasthole drill. In ICAPS 2009 - Proceedings of the 19th International Conference on Automated Planning and Scheduling (pp. 342–345). AAAI Press. https://doi.org/10.1609/icaps.v19i1.13388

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