Continuous mapping and localization for autonomous navigation in rough terrain using a 3D laser scanner

For autonomous navigation in difficult terrain, such as degraded environments in disaster response scenarios, robots are required to create a map of an unknown environment and to localize within this map. In this paper, we describe our approach to simultaneous localization and mapping that is based on the measurements of a 3D laser-range finder. We aggregate laser-range measurements by registering sparse 3D scans with a local multiresolution surfel map that has high resolution in the vicinity of the robot and coarser resolutions with increasing distance, which corresponds well to measurement density and accuracy of our sensor. By modeling measurements by surface elements, our approach allows for efficient and accurate registration and leverages online mapping and localization. The incrementally built local dense 3D maps of nearby key poses are registered against each other. Graph optimization yields a globally consistent dense 3D map of the environment. Continuous registration of local maps with the global map allows for tracking the 6D robot pose in real time. We assess the drivability of the terrain by analyzing height differences in an allocentric height map and plan cost-optimal paths. The system has been successfully demonstrated during the DARPA Robotics Challenge and the DLR SpaceBot Camp. In experiments, we evaluate accuracy and efficiency of our approach. A complete system for continuous mapping and localization fully integrated.Allocentric mapping system to allow for continuous mapping and localization.Experiments from the DARPA Robotics Challenge Finals and DLR SpaceBot Camp 2015.

[1]  Jochen Kläß,et al.  Efficient Mobile Robot Navigation using 3D Surfel Grid Maps , 2012, ROBOTIK.

[2]  Panagiotis Papadakis,et al.  Terrain traversability analysis methods for unmanned ground vehicles: A survey , 2013, Eng. Appl. Artif. Intell..

[3]  Jörg Stückler,et al.  Multi-resolution surfel mapping and real-time pose tracking using a continuously rotating 2D laser scanner , 2013, 2013 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR).

[4]  Sven Behnke,et al.  Intuitive bimanual telemanipulation under communication restrictions by immersive 3D visualization and motion tracking , 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

[5]  Christopher M. Bishop,et al.  Pattern Recognition and Machine Learning (Information Science and Statistics) , 2006 .

[6]  R. Siegwart,et al.  ROBOT-CENTRIC ELEVATION MAPPING WITH UNCERTAINTY ESTIMATES , 2014 .

[7]  Paul Newman,et al.  Using laser range data for 3D SLAM in outdoor environments , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[8]  Radu Horaud,et al.  Joint Registration of Multiple Point Sets , 2016, ArXiv.

[9]  Achim J. Lilienthal,et al.  Maximum likelihood point cloud acquisition from a mobile platform , 2009, 2009 International Conference on Advanced Robotics.

[10]  Jörg Stückler,et al.  Multilayered Mapping and Navigation for Autonomous Micro Aerial Vehicles , 2016, J. Field Robotics.

[11]  Andriy Myronenko,et al.  Point Set Registration: Coherent Point Drift , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Michael Bosse,et al.  Continuous 3D scan-matching with a spinning 2D laser , 2009, 2009 IEEE International Conference on Robotics and Automation.

[13]  Christopher Brunskill,et al.  Terrain trafficability analysis and soil mechanical property identification for planetary rovers: A survey , 2012 .

[14]  Radu Horaud,et al.  Rigid and Articulated Point Registration with Expectation Conditional Maximization , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Stefan Kohlbrecher,et al.  A flexible and scalable SLAM system with full 3D motion estimation , 2011, 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics.

[16]  Wolfram Burgard,et al.  G2o: A general framework for graph optimization , 2011, 2011 IEEE International Conference on Robotics and Automation.

[17]  Jörg Stückler,et al.  NimbRo Explorer: Semiautonomous Exploration and Mobile Manipulation in Rough Terrain , 2015, J. Field Robotics.

[18]  Tom Duckett,et al.  Scan registration for autonomous mining vehicles using 3D-NDT: Research Articles , 2007 .

[19]  Wolfram Burgard,et al.  Multi-Level Surface Maps for Outdoor Terrain Mapping and Loop Closing , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[20]  Wolfram Burgard,et al.  OctoMap: an efficient probabilistic 3D mapping framework based on octrees , 2013, Autonomous Robots.

[21]  A. Nuchter,et al.  6D SLAM with approximate data association , 2005, ICAR '05. Proceedings., 12th International Conference on Advanced Robotics, 2005..

[22]  Tom Duckett,et al.  Scan registration for autonomous mining vehicles using 3D‐NDT , 2007, J. Field Robotics.

[23]  Maxim Likhachev,et al.  Efficiently Using Cost Maps For Planning Complex Maneuvers , 2008 .

[24]  Wolfram Burgard,et al.  An Efficient Extension to Elevation Maps for Outdoor Terrain Mapping and Loop Closing , 2007, Int. J. Robotics Res..

[25]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Jörg Stückler,et al.  Local Multi-resolution Surfel Grids for MAV Motion Estimation and 3D Mapping , 2014, IAS.

[27]  Achim J. Lilienthal,et al.  Path planning in 3D environments using the Normal Distributions Transform , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[28]  Huosheng Hu,et al.  3D mapping with multi-resolution occupied voxel lists , 2010, Auton. Robots.

[29]  Takeo Kanade,et al.  Terrain mapping for a roving planetary explorer , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[30]  Achim J. Lilienthal,et al.  Fast and accurate scan registration through minimization of the distance between compact 3D NDT representations , 2012, Int. J. Robotics Res..

[31]  Piotr Skrzypczynski,et al.  Estimating terrain elevation maps from sparse and uncertain multi-sensor data , 2012, 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[32]  Jörg Stückler,et al.  Local multi-resolution representation for 6D motion estimation and mapping with a continuously rotating 3D laser scanner , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[33]  John Amanatides,et al.  A Fast Voxel Traversal Algorithm for Ray Tracing , 1987, Eurographics.

[34]  Brian P. Gerkey.  Planning and Control in Unstructured Terrain , 2008 .

[35]  Tim D. Barfoot,et al.  Towards relative continuous-time SLAM , 2013, 2013 IEEE International Conference on Robotics and Automation.

[36]  Jinhan Lee,et al.  Cost based planning with RRT in outdoor environments , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[37]  Michael Beetz,et al.  Leaving Flatland: Efficient real‐time three‐dimensional perception and motion planning , 2009, J. Field Robotics.

[38]  Andreas Nüchter,et al.  6DOF semi-rigid SLAM for mobile scanning , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[39]  Jörg Stückler,et al.  Multi-resolution surfel maps for efficient dense 3D modeling and tracking , 2014, J. Vis. Commun. Image Represent..

[40]  Paul Newman,et al.  Lost in translation (and rotation): Rapid extrinsic calibration for 2D and 3D LIDARs , 2012, 2012 IEEE International Conference on Robotics and Automation.

[41]  Maren Bennewitz,et al.  Navigation in three-dimensional cluttered environments for mobile manipulation , 2012, 2012 IEEE International Conference on Robotics and Automation.