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2019 | OriginalPaper | Chapter

Planar Pose Estimation Using Object Detection and Reinforcement Learning

Authors : Frederik Nørby Rasmussen, Sebastian Terp Andersen, Bjarne Grossmann, Evangelos Boukas, Lazaros Nalpantidis

Published in: Computer Vision Systems

Publisher: Springer International Publishing

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Abstract

Pose estimation concerns systems or models dealing with the determination of a static object’s pose using, in this case, vision. This paper approaching the problem with an active vision-based solution, that integrates both perception and action in the same model. The problem is solved using a combination of neural networks for object detection and a reinforcement learning architecture for moving a camera and estimating the pose. A robotic implementation of the proposed active vision system is used for testing with promising results. Experiments show that our approach does not only solve the simple task of planar visual pose estimation, but also exhibits robustness to changes in the environment.

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Boukas, E., Gasteratos, A.: Modeling regions of interest on orbital and rover imagery for planetary exploration missions. Cybern. Syst. 47(3), 180–205 (2016). https://doi.org/10.1080/01969722.2016.1154771CrossRef

Brockman, G., et al.: OpenAI Gym (2016)

Brooks, R.A.: Intelligence without representation. Artif. Intell. 47, 139–159 (1991)CrossRef

Huang, J., et al.: Speed/accuracy trade-offs for modern convolutional object detectors. In: Computer Vision and Pattern Recognition (2017)

Jia, Z., Chang, Y.J., Chen, T.: Active view selection for object and pose recognition. In: 2009 IEEE 12th International Conference on Computer Vision Workshops, September 2009, pp. 641–648 (2009)

Kostavelis, I., Nalpantidis, L., Gasteratos, A.: Object recognition using saliency maps and HTM learning. In: IEEE International Conference on Imaging Systems and Techniques, pp. 528–532. IEEE, Manchester (2012)

Krull, A., Brachmann, E., Michel, F., Yang, M.Y., Gumhold, S.: Learning analysis-by-synthesis for 6D pose estimation in RGB-D images. In: 2015 IEEE International Conference on Computer Vision, December 2015, pp. 954–962 (2015)

Krull, A., Brachmann, E., Nowozin, S., Michel, F., Shotton, J., Rother, C.: PoseAgent: budget-constrained 6D object pose estimation via reinforcement learning. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition, July 2017, pp. 2566–2574 (2017)

Mnih, V., et al.: Human-level control through deep reinforcement learning. Nature 518(7540), 529–533 (2015). https://doi.org/10.1038/nature14236CrossRef

10.

Piater, J., Jodogne, S., Detry, R., Kraft, D., Krueger, N., Kroemer, O.: Learning visual representations for perception-action systems. Int. J. Robot. Res. 30, 294–307 (2015)CrossRef

11.

Plappert, M.: Keras-RL (2016). https://github.com/keras-rl/keras-rl

12.

Polydoros, A.S., Boukas, E., Nalpantidis, L.: Online multi-target learning of inverse dynamics models for computed-torque control of compliant manipulators. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver (2017)

13.

Toshev, A., Szegedy, C.: DeepPose: human pose estimation via deep neural networks. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, June 2014, pp. 1653–1660 (2014)

14.

Tremblay, J., To, T., Sundaralingam, B., Xiang, Y., Fox, D., Birchfield, S.: Deep object pose estimation for semantic robotic grasping of household objects. Cornell University Library (2018)

15.

Wooldridge, M., Jennings, N.R.: Agent theories, architectures, and languages: a survey. In: Wooldridge, M.J., Jennings, N.R. (eds.) ATAL 1994. LNCS, vol. 890, pp. 1–39. Springer, Heidelberg (1995). https://doi.org/10.1007/3-540-58855-8_1CrossRef

Title: Planar Pose Estimation Using Object Detection and Reinforcement Learning
Authors: Frederik Nørby Rasmussen
Sebastian Terp Andersen
Bjarne Grossmann
Evangelos Boukas
Lazaros Nalpantidis
Publisher: Springer International Publishing
Book: Computer Vision Systems
Print ISBN: 978-3-030-34994-3

Electronic ISBN: 978-3-030-34995-0

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-34995-0_32

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