Abstract
Dynamic Vision Sensor (DVS) is a promising neuromorphic vision sensor for autonomous locomotion control of mobile robots, as the DVS acquires visual information by mimicking retina to sense and encode the world as neural signals. In this paper, we present an autonomous target detecting and tracking control approach for a snake-like robot with a monocular DVS. By using Hough transform based on the Spiking Neural Network (SNN), the target pole is detected as two parallel lines from the event-based visual input. Then a depth estimation method based on the pose and motion of the robot is proposed. Furthermore, by combining the periodic motion feature of the snake-like robot, an adaptive tracking method based on the estimated depth information is introduced. Experiments are conducted on a snake-like robot to demonstrate the practicality and accuracy of our proposed method to track a target pole dynamically with a monocular DVS.
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
Similar content being viewed by others
References
Liljebäck, P., Pettersen, K.Y., Stavdahl, O., Gravdahl, J.T.: Snake Robots: Modelling, Mechatronics, and Control. Springer Science & Business Media, Heidelberg (2012)
Ponte, H., Queenan, M., Gong, C., Mertz, C., Travers, M., Enner, F.: Visual sensing for developing autonomous behavior in snake robots. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 2779–2784. IEEE (2014)
Pfotzer, L., Klemm, S., Rönnau, A., Zöllner, J.M., Dillmann, R.: Autonomous navigation for reconfigurable snake-like robots in challenging, unknown environments. Robot. Auton. Syst. 89, 123–135 (2017)
Weikersdorfer, D., Adrian, D.B., Cremers, D., Conradt, J.: Event-based 3D SLAM with a depth-augmented dynamic vision sensor. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 359–364. IEEE (2014)
Seifozzakerini, S., Yau, W.Y., Zhao, B., Mao, K.: Event-based hough transform in a spiking neural network for multiple line detection and tracking using a dynamic vision sensor. In: BMVC (2016)
Everding, L., Walger, L., Ghaderi, V.S., Conradt, J.: A mobility device for the blind with improved vertical resolution using dynamic vision sensors. In: 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom), pp. 1–5. IEEE (2016)
Piatkowska, E., Belbachir, A., Gelautz, M.: Asynchronous stereo vision for event-driven dynamic stereo sensor using an adaptive cooperative approach. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 45–50 (2013)
Wiesmann, G., Schraml, S., Litzenberger, M., Belbachir, A.N., Hofstatter, M., Bartolozzi, C.: Event-driven embodied system for feature extraction and object recognition in robotic applications. In: Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 76–82. IEEE (2012)
Auerbach, J.: Cross tracking on the DVS using an extended hough space method. In: Telluride Nueromorphic Cognition Engineering Workshop (2009)
Conradt, J., Galluppi, F., Stewart, T.C.: Trainable sensorimotor mapping in a neuromorphic robot. Robot. Auton. Syst. 71, 60–68 (2015)
Maass, W.: Networks of spiking neurons: the third generation of neural network models. Neural Netw. 10(9), 1659–1671 (1997)
Burkitt, A.N.: A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input. Biol. Cybern. 95(1), 1–19 (2006)
Bing, Z., Cheng, L., Huang, K., Zhou, M., Knoll, A.: CPG-based control of smooth transition for body shape and locomotion speed of a snake-like robot. In: 2017 IEEE International Conference on Robotics and Automation (ICRA), pp. 4146–4153. IEEE (2017)
Bing, Z., Cheng, L., Chen, G., Röhrbein, F., Huang, K., Knoll, A.: Towards autonomous locomotion: CPG-based control of smooth 3D slithering gait transition of a snake-like robot. Bioinspir. Biomim. 12(3), 035001 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Jiang, Z., Bing, Z., Huang, K., Chen, G., Cheng, L., Knoll, A. (2017). Event-Based Target Tracking Control for a Snake Robot Using a Dynamic Vision Sensor. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10639. Springer, Cham. https://doi.org/10.1007/978-3-319-70136-3_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-70136-3_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-70135-6
Online ISBN: 978-3-319-70136-3
eBook Packages: Computer ScienceComputer Science (R0)