Abstract
In this paper, a method for unknown object detection based on impacting and keypoint tracking is presented. In this method, a robot perturbs object positions by punching the floor on which the objects are placed, to detect each of the objects individually from camera images before and after the punching. The detection method utilizes consistent movements of the keypoints of each object according to its rigid-body motion. After the detection, a grasp of each of the detected objects is planned based on extracting its two parallel edges. The proposed method is successfully applied to picking up of mahjong tiles by an industrial manipulator.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
OpenCV. http://opencv.org/
Arun, K.S., Huang, T.S., Blostein, S.D.: Least-squares fitting of two 3-D point sets. IEEE Trans. Pattern Anal. Mach. Intell. 9(5), 698–700 (1987)
Bohg, J., Hausman, K., Sankaran, B., Brock, O., Kragic, D., Schaal, S., Sukhatme, G.S.: Interactive perception: leveraging action in perception and perception in action. IEEE Trans. Robotic. 33(6), 1273–1291 (2017)
Chang, L., Smith, J.R., Fox, D.: Interactive singulation of objects from a pile. In: Proceedings of 2012 IEEE International Conference on Robotics and Automation, pp. 3875–3882 (2012)
Edelsbrunner, H., Kirkpatrick, D., Seidel, R.: On the shape of a set of points in the plane. IEEE Trans. Inf. Theor. 29(4), 551–559 (1983)
Gupta, M., Müller, J., Sukhatme, G.S.: Using manipulation primitives for object sorting in cluttered environments. IEEE Trans. Autom. Sci. Eng. 12(2), 608–614 (2015)
Harada, K., Tsuji, T., Nagata, K., Yamanobe, N., Maruyama, K., Nakamura, A., Kawai, Y.: Grasp planning for parallel grippers with flexibility on its grasping surface. In: Proceedings of IEEE International Conference on Robotics and Biomimetics, pp. 1540–1546 (2011)
Harris, C., Stephens, M.: A combined corner and edge detector. In: Proceedings of Fourth Alvey Vision Conference, pp. 147–151 (1988)
Hermans, T., Rehg, J.M., Bobick, A.: Guided pushing for object singulation. In: Proceedings of 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4783–4790 (2012)
Katz, D., Venkatraman, A., Kazemi, M., Bagnell, J.A., Stentz, A.: Perceiving, learning, and exploiting object affordances for autonomous pile manipulation. Auton. Robots 37(4), 369–382 (2014)
Lowe, D.G.: Object recognition from local scale invariant features. In: Proceedings of 1999 IEEE International Conference on Computer Vision, pp. 1150–1157 (1999)
Metta, G., Fitzpatrick, P.: Better vision through manipulation. Adapt. Behav. 11(2), 109–128 (2003)
Schiebener, D., Ude, A., Asfour, T.: Physical interaction for segmentation of unknown textured and non-textured rigid objects. In: Proceedings of 2014 IEEE International Conference on Robotics and Automation, pp. 4959–4966 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Maeda, Y., Tsuruga, H., Honda, H., Hirono, S. (2019). Unknown Object Detection by Punching: An Impacting-Based Approach to Picking Novel Objects. In: Strand, M., Dillmann, R., Menegatti, E., Ghidoni, S. (eds) Intelligent Autonomous Systems 15. IAS 2018. Advances in Intelligent Systems and Computing, vol 867. Springer, Cham. https://doi.org/10.1007/978-3-030-01370-7_52
Download citation
DOI: https://doi.org/10.1007/978-3-030-01370-7_52
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01369-1
Online ISBN: 978-3-030-01370-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)