UGV-MAV Collaboration for Augmented 2D Maps

Over the past couple of years, with the development of efficient control algorithms, micro aerial vehicles have come into the picture. In this paper, we consider the problem of creating a map of an indoor environment which provides more information than a 2D map and at the same time is more accurate than the contemporary 3D mapping algorithms. We propose a novel collaborative system, consisting of an unmanned ground vehicle and a micro aerial vehicle, which is used to create augmented 2D maps using the distinct sensing capabilities of these two robots. This system works in a collaborative manner such that the two robots complement each others movement and sensing capabilities.

[1]  Jan Faigl,et al.  AR-Drone as a Platform for Robotic Research and Education , 2011, Eurobot Conference.

[2]  H.G. Tanner,et al.  Cooperation between Aerial and Ground vehicle groups for Reconnaissance missions , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[3]  Heinrich Niemann,et al.  Point Set Registration with Integrated Scale Estimation , 2005 .

[4]  Roland Siegwart,et al.  Fusion of IMU and Vision for Absolute Scale Estimation in Monocular SLAM , 2011, J. Intell. Robotic Syst..

[5]  Vijay Kumar,et al.  Trajectory Generation and Control for Precise Aggressive Maneuvers with Quadrotors , 2010, ISER.

[6]  Luiz Chaimowicz,et al.  Deploying Air-Ground Multi-Robot Teams in Urban Environments , 2005 .

[7]  Wolfram Burgard,et al.  Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters , 2007, IEEE Transactions on Robotics.

[8]  Albert S. Huang,et al.  Visual Odometry and Mapping for Autonomous Flight Using an RGB-D Camera , 2011, ISRR.

[9]  Radu Bogdan Rusu,et al.  3D is here: Point Cloud Library (PCL) , 2011, 2011 IEEE International Conference on Robotics and Automation.

[10]  Jun-Sik Kim,et al.  Complementation of cameras and lasers for accurate 6D SLAM: From correspondences to bundle adjustment , 2011, 2011 IEEE International Conference on Robotics and Automation.

[11]  Roland Siegwart,et al.  Intuitive 3D Maps for MAV Terrain Exploration and Obstacle Avoidance , 2011, J. Intell. Robotic Syst..

[12]  G. Klein,et al.  Parallel Tracking and Mapping for Small AR Workspaces , 2007, 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality.

[13]  Nico Blodow,et al.  Towards 3D Point cloud based object maps for household environments , 2008, Robotics Auton. Syst..

[14]  H.H.T. Liu,et al.  A cooperative UAV/UGV platform for wildfire detection and fighting , 2008, 2008 Asia Simulation Conference - 7th International Conference on System Simulation and Scientific Computing.