Hector SLAM ppt

【实例简介】
关于Hector SLAM的ppt,介绍了hector slam的功能和框架。
影 TECHNISCHE Background 给 UNIVERSITAT DARMSTADT Team Hector is part of the rtg1362: Cooperative, adaptive and Responsive Monitoring in Mixed Mode environments monitorIng Surveillance esearchtreseue heterogeneity Sensing Monitoring(A) Foundations of Computing Communication( B) Middleware(C) Cooperative Planning& control (D mobility, complexity motes stationary sensors MVS UAVS UGVs issiorroentro Hector SLAM Tutorial Stefan KohIbrecher Ros Workshop Graz 22/08/2012 3 Example TECHNISCHE 给 UNIVERSITAT Monitoring in Normal Operation DARMSTADT Hector SLAM Tutorial Stefan KohIbrecher Ros Workshop Graz 22/08/2012 Example 影 TECHNISCHE 给 UNIVERSITAT Some Monitoring Elements and Channels Knocked-Out DARMSTADT Ⅹ为Ⅹ ■■ Hector SLAM Tutorial Stefan KohIbrecher Ros Workshop Graz 22/08/2012 5 Motivation 影 TECHNISCHE 给 UNIVERSITAT Deployment of Additional Equipment (Robots, Sensors) DARMSTADT Motivates fundamental research questions being addressed by our RTG 身 Hector SLAM Tutorial Stefan KohIbrecher Ros Workshop Graz 22/08/2012 6 影 TECHNISCHE Team Hector 给 UNIVERSITAT DARMSTADT Hector: Heterogeneous cooperating Team of Robots Established in fall 2008 Transition from robo frame to ros as the central middleware since late 2010 You can also like follow us on facebook http://www.facebook.com/teamhectordarmstadt;) Hector SLAM Tutorial Stefan KohIbrecher Ros Workshop Graz 22/08/2012 影 TECHNISCHE Team Hector 给 UNIVERSITAT DARMSTADT 1st place in the European Micro Air 3rd place(out of 12& 16 teams)at the Vehicle Conference(EMAV) in category SICK Company's Robot Day, October 2009 Outdoor Autonomy, Sep. 2009, Delft 2010. Wald kirch 3 2nd place(out of 27)"Best in Class Autonomy 'at RoboCup 2010, Singapore Winner and Best in Class Autonomy at Robocup 2011 GermanOpen 2nd place "Best in Class autonomy ' at RoboCup 2011, Istanbul Hector SLAM Tutorial Stefan KohIbrecher Ros Workshop Graz 22/08/2012 8 Requirements- SLAM in USAR 影 TECHNISCHE 给 UNIVERSITAT environments DARMSTADT SLAM >Map the environment >Localize robot >Realtime capable Harsh Terrain >Full 6DOF pose estimation Cannot rely on( wheel/drivetrain )odometry Robustness Primary mission is search for victims /exploration >Mapping/Localization should not interfere Georeferenced Map with robot trajectory and objects of interest Saving GeoTiff maps Hector SLAM Tutorial Stefan KohIbrecher Ros Workshop Graz 22/08/2012 影 TECHNISCHE Requirements- Related Work 给 UNIVERSITAT DARMSTADT Mapping(2D SLAM, Rao-Blackwellized particle filter) Odometry needed (can be simulated through separate scanmatcher) Robot pose and map data jump" relative to map frame 5. 7. e 2 Does not leverage high scan rates of modern LIdars T9EEEL E 6D SLAM Requires acquisition of 3d Laser scans of the environment mpairs mobility of platform Sensitive to correct parameter settings Visual slam Not robust enough High CPu load Promising improvements lately Hector SLAM Tutorial Stefan KohIbrecher Ros Workshop Graz 22/08/2012 10 【实例截图】
【核心代码】