Non-Collision Path Planning of a Payload in Crane Operating Space

Jaroslaw Smoczek; Janusz Szpytko; Pawel Hyla

doi:10.4028/www.scientific.net/SSP.198.559

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HomeSolid State PhenomenaSolid State Phenomena Vol. 198Non-Collision Path Planning of a Payload in Crane...

Non-Collision Path Planning of a Payload in Crane Operating Space

Abstract:

The problem of ensuring the safe and efficient cranes operations in automated manufacturing processes involves the automation of the operating workspace identification, non-collision and time-optimal path planning, and real-time following a payload along the determined path by crane motion mechanisms with expected precision. The paper describes the stereo vision based system used for identification of workspace of the laboratory scaled overhead travelling crane. The time-optimal trajectory of a payload is determined by using the A-star graph searching algorithm, and next real-time trucking by PLC-based crane control system.

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Periodical:

Solid State Phenomena (Volume 198)

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559-564

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https://doi.org/10.4028/www.scientific.net/SSP.198.559

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Online since:

March 2013

Authors:

Jaroslaw Smoczek, Janusz Szpytko, Pawel Hyla

Keywords:

A-Star Algorithm, Dense Disparity Map, Graph Search, Vision System

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References

[1] C. Atzeni, G. Guidi, M. Pieraccini, 3D Digitizing of cultural heritage, Journal of Cultural Heritage, 2/1, (2001), 63-70.

DOI: 10.1016/s1296-2074(01)01108-6

Google Scholar

[2] J. J. Aguilar, M. Lope, F. Torres, A. Blesa, Development of a stereovision system for non-contact railway concrete sleepers measurement based in holographic optical elements, Measurement, 38/2 (2005), 154-165.

DOI: 10.1016/j.measurement.2005.04.006

Google Scholar

[3] R. Dechter, P. Judea, Generalized best-first search strategies and the optimality of A*, Journal of the ACM 32(3), 1985, 505–536.

DOI: 10.1145/3828.3830

Google Scholar

[4] M. Hu, G. Penney, M. Figl, P. Edwards, Reconstruction of a 3D surface from video that is robust to missing data and outliers: Application to minimally invasive surgery using stereo and mono endoscopes, Medical Image Analysis, 16/3, (2012).

DOI: 10.1016/j.media.2010.11.002

Google Scholar

[5] S. Kudoh, K. Ogawara, M. Ruchanurucks, K. Ikeuchi, Painting robot with multi-fingered hands and stereo vision, Robotics and Autonomous Systems, In IEEE International Conference on Multisensor Fusion and Integration, 57 (2009), 279-288.

DOI: 10.1016/j.robot.2008.10.007

Google Scholar

[6] L.H. Lin, P.D. Lawrence, R. Hall, Stereo vision based swing angle sensor for mining rope shovel, Proceedings of the RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan (2010), 1714-1721.

DOI: 10.1109/iros.2010.5650457

Google Scholar

[7] J. McBride, M. Snorrason, T. Goodsell, R. Eaton, M. R. Stevens, Single camera stereo for mobile robot surveillance, In Proceedings of IEEE International Conference on Robotics and Automation (ICRA 2003), Vol. 1, 139-144.

DOI: 10.1109/cvpr.2005.527

Google Scholar

[8] C. F. Olson, H. Abi-Rached, M. Ye, J. P. Hendrich, Wide-baseline stereo vision for Mars rovers. In Proceedings of International Conference on Intelligent Robots and Systems (IROS 2003), Vol. 2, 1302–1307.

DOI: 10.1109/iros.2003.1248825

Google Scholar

[9] F. Rovira-Más, Q. Zhang, J. F. Reid, Stereovision three-dimensional terrain maps for precision agriculture, Computers and Electronics in Agriculture, 60/3 (2008), 133-143.

DOI: 10.1016/j.compag.2007.07.007

Google Scholar

[10] J. Smoczek, J. Szpytko, Heuristic approach to trajectory planning of n-th numerous set of automated cranes, Journal of KONBiN, No. 2, 3 (14, 15), 2010, 267–278.

DOI: 10.2478/v10040-008-0183-7

Google Scholar