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Clustering Analysis for Secondary Breaking Using a Low-Cost Time-of-Flight Camera

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication2018 Ninth International Conference on Intelligent Control and Information Processing (ICICIP)
PublisherIEEE
Pages318-324
Number of pages7
ISBN (Electronic)978-1-5386-5860-4
ISBN (Print)978-1-5386-5861-1
DOIs
Publication statusPublished - Nov 2018
Publication typeA4 Article in a conference publication
EventInternational Conference on Intelligent Control and Information Processing -
Duration: 1 Jan 1900 → …

Conference

ConferenceInternational Conference on Intelligent Control and Information Processing
Period1/01/00 → …

Abstract

The integration of robust perception in a heavy-duty manipulation control system is an enabler for autonomous mining. This paper aims to analyze performance and robustness of clustering methods for object recognition during the secondary breaking stage of mining. Secondary breaking refers to breaking over-sized rocks into smaller pieces for the purpose of grinding and extraction of valuable ores and minerals. Therefore, recognition of rock pieces is the detection of unstructured targets within a structured environment. The clustering methods are experimentally evaluated by several sets of scenes of point clouds as outputs of a Time-of-Flight camera (ToF). The challenges of rock detection from sparse 3D point cloud data are addressed. In outdoor conditions, ToFs generally provide coarse but robust output in short sample times. Therefore, some clustering methods can be prone to numerical and statistical errors. This paper highlights the weaknesses and strengths of three methods for the secondary breaking application. We propose an algorithmic method for exploiting the existing clustering and segmentation methods efficiently in the detection loop to determine a suitable contact point and approaching angle for a hydraulic jack hammer. The results verify effectiveness of the proposed approach for scattered outputs of low-cost ToFs.

Keywords

  • Three-dimensional displays, Rocks, Cameras, Clustering methods, Clustering algorithms, Gaussian mixture model, Range sensing, time-of-flight camera, automatic extraction, 3D point clouds, clustering.

Publication forum classification

Field of science, Statistics Finland