Abstract
Current operations in rail yards are dangerous and limited by the operational capabilities of humans being able to perform safely in harsh conditions while maintain high productivity. Such issues call out the need for robust and capable autonomous systems. In this paper, we outline one such autonomous solution for the railroad domain, capable of performing the brake bleeding inspection task in a hump yard. Towards that, we integrated a large form factor mobile robot (the Clearpath Grizzly) with an industrial manipulator arm (Yasakawa Motoman SIA20F) to effectively detect, identify and subsequently manipulate the brake lever under harsh outdoor environments. In this paper, we focus on the system design and the core algorithms necessary for reliable and repeatable system execution. To test our developed solution, we performed extensive field tests in a fully operational rail yard with randomly picked rail cars under day and night-time conditions. The results from the testing are promising and validate the feasibility of deploying an autonomous brake bleeding solution for railyards.
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References
Oum, T.H., Waters, W.G., Yum, C.: A survey of productivity and efficiency measurement in rail transport. J. Transp. Econ. Policy 9–42 (1999)
Drudi, D.: Railroad-related work injury fatalities. Monthly Lab. Rev. 130, 17 (2007)
Thorpe, C., Durrant-Whyte, H.: Field robots. In: Proceedings of the 10th International Symposium of Robotics Research (ISRR’01) (2001)
Meeussen, W., Wise, M., Glaser, S., Chitta, S., McGann, C., Mihelich, P., Marder-Eppstein, E.: Autonomous door opening and plugging in with a personal robot. In: Proceedings of 2010 IEEE International Conference on Robotics and Automation (ICRA), pp. 729–736 (2010)
Srinivasa, S.S., Ferguson, D., Helfrich, C.J., Berenson, D., Collet, A., Diankov, R., Gallagher, G., Hollinger, G., Kuffner, J., Weghe, M.V.: HERB: a home exploring robotic butler. Auton Robots 28(1), 5–20 (2010)
Nguyen, H., Anderson, C., Trevor, A., Jain, A., Xu, Z., Kemp, C.C.: El-E: an assistive robot that fetches objects from flat surfaces. In: Proceedings of the 2008 International Conference on Human-Robot Interaction (2008)
Pedersen, S.M., Fountas, S., Have, H., Blackmore, B.S.: Agricultural robots: an economic feasibility study. Precis. Agric. 5, 589–595 (2002)
Blackmore, B.S.: A systems view of agricultural robots. In: Proceedings 6th European Conference on Precision Agriculture (ECPA), pp. 23–31 (2007)
Redhead, F., Snow, S., Vyas, D., Bawden, O., Russell, R., Perez, T., Brereton, M.: Bringing the farmer perspective to agricultural robots. In: Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, pp. 1067–1072 (2015)
Green, J.: Underground mining robot: a CSIR project. In; Proceedings of 2012 IEEE International Symposium on Safety, Security, and Rescue Robotics, pp. 1–6 (2012)
Skonieczny, K., Delaney, M., Wettergreen, D.S., “Red” Whittaker, W.L.: Productive lightweight robotic excavation for the moon and mars. J. Aerosp. Eng. 27(4) (2013)
Jensen, M.A., Falk, D.B., Sørensen, C.G., Blas, M.R., Lykkegaard, K.L.: In-field and inter-field path planning for agricultural transport units. Comput. Ind. Eng. 63(4), 1054–1061 (2012)
Suessemilch, I., Rohrer, C., Roesch, R., Guenther, C., Von Collani, Y., Linder, S., Fischer, V.: Projection unit for a self-directing mobile platform, transport robot and method for operating a self-directing mobile platform. U.S. Patent Application 14/447,501, filed 30 July 2014 (2014)
Pratt, G., Manzo, J.: The DARPA robotics challenge [competitions]. IEEE Robot. Autom. Mag. 20(2), 10–12 (2013)
Johnson, M., Shrewsbury, B., Bertrand, S., Tingfan, W., Duran, D., Floyd, M., Abeles, P.: Team IHMC’s lessons learned from the DARPA robotics challenge trials. J. Field Robot. 32(2), 192–208 (2015)
Labbe, M., Michaud, F.: Online global loop closure detection for large-scale multi-session graph-based slam. In: Proceedings of 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2661–2666 (2014)
Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. Int. J. Robot. Res. 5(1), 90–98 (1986)
Li, S., Jain, A., Sharma, P., Sen, S.: Robust Object Detection in Industrial Environments by Using a Mobile Robot (2016)
Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. Adv. Neural Inf. Process. Syst. 1097–1105 (2012)
LeCun, Y., Bengio, Y.: Convolutional networks for images, speech, and time series. In: The Handbook of Brain Theory and Neural Networks 10 (1995)
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., Fei-Fei, L.: Imagenet: A large-scale hierarchical image database. In: Proceedings of 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 248–255 (2009)
Felzenszwalb, P., McAllester, D., Ramanan, D.: A discriminatively trained, multiscale, deformable part model. In: Proceedings of 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)
Wohlkinger, W., Vincze, M.: Ensemble of shape functions for 3D object classification. In: Proceedings of 2011 IEEE International Conference on Robotics and Biomimetics, pp. 2987–2992 (2011)
Suykens, J.A.K., Vandewalle, J.: Least squares support vector machine classifiers. Neural Process. Lett. 9(3), 293–300 (1999)
Stein, S., Worgotter, F., Schoeler, M., Papon, J., Kulvicius, T.: Convexity based object partitioning for robot applications. In: Proceedings of 2014 IEEE International Conference on Robotics and Automation, pp. 3213–3220 (2014)
Rusu, R.B., Cousins, S.: 3D is here: Point cloud library (PCL). In: Proceedings of 2011 IEEE International Conference on Robotics and Automation (ICRA), pp. 1–4 (2011)
Wurm, K.M., Hornung, A., Bennewitz, M., Stachniss, C., Burgard, W.: OctoMap: a probabilistic, flexible, and compact 3D map representation for robotic systems. In: Proceedings of the 2010 ICRA Workshop on Best Practice in 3D Perception and Modeling for Mobile Manipulation, vol. 2 (2010)
Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: ROS: an open-source Robot Operating System. In: Proceedings of 2009 ICRA Workshop on Open Source Software, vol. 3, no. 2, p. 5 (2009)
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Tan, H. et al. (2017). An Integrated Robotic System for Autonomous Brake Bleeding in Rail Yards. In: Chen, W., Hosoda, K., Menegatti, E., Shimizu, M., Wang, H. (eds) Intelligent Autonomous Systems 14. IAS 2016. Advances in Intelligent Systems and Computing, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-319-48036-7_12
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DOI: https://doi.org/10.1007/978-3-319-48036-7_12
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