Detection of Large Bodies of Water for Heterogeneous Swarm Applications
Abstract
Multiple robot systems are becoming popular, as introducing more robots into a system generally means that the system is able to finish a task quickly, as well as making the system more robust. Generally, these systems are homogenous in nature as they are easier to build, test and conceptualise. More applications of these types of systems in a heterogeneous sense is becoming a must, as these robots are acting in more than one medium such as on land and underwater. In this paper a subsystem of a heterogeneous swarm is investigated where a land based robot is to drive up to the edge of a pool and stop autonomously, allowing for the transfer of an object from an underwater robot. To detect the edge of a pool an Xbox Kinect sensor is used as it was found that by using the IR feed of the camera the problem becomes significantly simpler.
References
[1] A. Dancu, M. Fourgeaud, Z. Franjcic, and R. Avetisyan, Underwater reconstruction using depth sensors, in SIGGRAPH Asia 2014 Technical Briefs, 2014, p. 2.
[2] A. L. Rankin, L. H. Matthies, and P. Bellutta, Daytime water detection based on sky reflections, in Robotics and Automation (ICRA), 2011 IEEE International Conference on, 2011, pp. 5329–5336.
[3] A. Rankin, and L. Matthies, Daytime water detection based on color variation, in Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on, 2010, pp. 215–221, (2010).
[4] P. Santana, R. Mendon, and J. Barata, Water detection with segmentation guided dynamic texture recognition, in Robotics and Biomimetics (ROBIO), 2012 IEEE International Conference on, 2012, pp. 1836–1841.
[5] R. Pombeiro, R. Mendon, P. Rodrigues, F. Marques, A. Louren, and E. Pinto, et al., Water detection from downwash-induced optical flow for a multirotor UAV, in OCEANS 2015 - MTS/IEEE Washington, 2015, pp. 1–6.
[6] J. Song, S. Na, K. Hong-Gab, H. Kim, and L. Chun-shin, A depth measurement system associated with a mono-camera and a rotating mirror, in Pacific-Rim Conference on Multimedia, 2002, pp. 1145–1152.
[7] J. Michels, A. Saxena, and A. Y. Ng, High speed obstacle avoidance using monocular vision and reinforcement learning, in Proceedings of the 22nd international conference on Machine learning, 2005, pp. 593–600.
[8] T. Nagai, T. Naruse, M. Ikehara, and A. Kurematsu, Hmm-based surface reconstruction from single images, in Image Processing. 2002. Proceedings. 2002 International Conference on, 2002, pp. II-561- II-564 vol. 2.
[9] D. An, A. Woodward, P. Delmas, G. Gimelfarb, and J. Morris, Comparison of active structure lighting mono and stereo camera systems: Application to 3d face acquisition, in 2006 Seventh Mexican International Conference on Computer Science, 2006, pp. 135–141.
[10] G. C. Gini, and A. Marchi, Indoor robot navigation with single camera vision, in PRIS, 2002, pp. 67–76.