Abstract
This paper discusses the estimation of the easily visible information for deciding action of unknown object grasping without all of predefined knowledge in a real situation. To estimate the easily visible information, active perception is an important concept. A conventional active perception method estimates an optimum sensing position to measure the accurate object information. However, a robot has to move all around the object to measure the accurate data beforehand. This is not realistic for a robot operation. On the other hand, a robot wants to know the most easily visible sensing position in the neighborhood of a current position to make a decision as soon as possible from a viewpoint of a robot action. As a first step, we propose an estimation of an easily visible information using a point cloud data of an object which is limited data. Now, we apply the unknown object detection method based on plane detection. And, we propose the graspability and the easily visible information estimation method from the point cloud data of the object. We verify the proposed method in a multiple object environment. The effectiveness of our proposal are discussed for grasping an unknown object.
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Mitsunaga, N., Miyashita, Z., Shinozawa, K., Miyashita, T., Ishiguro, H., Hagita, N.: What makes people accept a robot in a social environment. In: International Conference on Intelligent Robots and Systems, pp. 3336–3343 (2008)
Zhang, Z.: Microsoft kinect sensor and its effect. IEEE Multimedia 19(2), 4–10 (2012)
Jurie, F., Dhome, M.: Real time 3D template matching. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. I-791–I-796 (2001)
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981)
Xu, L., Oja, E.: Randomized hough transform (RHT): basic mechanisms, algorithms, and computational complexities. CVGIP Image Underst. 57(2), 131–154 (1993)
Lyudmila, M., Tine, L., Herman, B., Klaas, G., Joris, D.S.: A comparison of decision making criteria and optimization methods for active robotic sensing. In: Dimov, I.T., Lirkov, I., Margenov, S., Zlatev, Z. (eds.) NMA 2002. LNCS, vol. 2542, pp. 316–324. Springer, Heidelberg (2003)
Gupta, S., Arbelaez, P., Girshick, R., Malik, J.: Inferring 3D object pose in RGB-D images. Comput. Vis. Pattern Recogn. (2015). arXiv preprint arXiv:1502.04652
Alenya, G., Foix, S., Torras, C.: ToF cameras for active vision in robotics. Sens. Actuators, A 218, 10–22 (2014)
Atanasov, N., Sankaran, B., Pappas, G.J., Daniilidis, K.: Nonmyopic view planning for active object classification and pose estimation. IEEE Trans. Rob. 30(5), 1078–1090 (2014)
Masuta, H., Makino, S., Lim, H., Motoyoshi, T., Koyanagi, K., Oshima, T.: Unknown object extraction for robot partner using depth sensor. In: 4th International Conference on Informatics, Electronics &Vision (2015)
Masuta, H., Hiwada, E., Kubota, N.: Control architecture for human friendly robots based on interacting with human. In: Jeschke, S., Liu, H., Schilberg, D. (eds.) ICIRA 2011, Part II. LNCS, vol. 7102, pp. 210–219. Springer, Heidelberg (2011)
Oggier, T., Lehmann, M., Kaufmannn, R., Schweizer, M., Richter, M., Metzler, P., Lang, G., Lustenberger, F., Blanc, N.: An all-solid-state optical range camera for 3D-real-time imaging with sub-centimeter depth-resolution (SwissRanger). Proc. SPIE 5249, 534–545 (2003)
Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of the 1995 IEEE International Conference on Neural Networks, vol. 4, pp. 1942–1948 (1995)
Carello, C., Turvey, M.T.: Rotational invariants and dynamic touch. In: Touch, Representation and Blindness, pp. 27–66 (2000)
Masuta, H., Lim, H., Motoyoshi, T., Koyanagi, K., Oshima, T.: Invariant perception for grasping an unknown object using 3D depth sensor. In: 2015 IEEE Symposium Series on Computational Intelligence, pp. 122–129 (2015)
Takagi, T., Sugeno, M.: Derivation of fuzzy control rules from human operator’s control actions. In: Proceedings of the IFAC Symposium on Fuzzy Information, Knowledge Representation and Secision Analysis, vol. 6, pp. 55–60 (1983)
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Masuta, H., Motoyoshi, T., Koyanagi, K., Oshima, T., Lim, Ho. (2016). Direct Perception of Easily Visible Information for Unknown Object Grasping. In: Kubota, N., Kiguchi, K., Liu, H., Obo, T. (eds) Intelligent Robotics and Applications. ICIRA 2016. Lecture Notes in Computer Science(), vol 9835. Springer, Cham. https://doi.org/10.1007/978-3-319-43518-3_8
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DOI: https://doi.org/10.1007/978-3-319-43518-3_8
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