Technical Introduction to AriAnA Rescue Robot Team


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This document which is presented by Amir H. Soltanzadeh outlines the technical issues applied in AriAnA rescue robot team.

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Technical Introduction to AriAnA Rescue Robot Team

  1. 1. AriAnA Rescue Robot Team<br />Technical Introduction<br />Amir H. SoltanzadehRobotics Lab @ Engineering School<br />IAUCTB<br />
  2. 2. Outlines<br />Introduction to USAR Robotics<br />USAR as a real-world problem<br />RoboCup Rescue Robot League<br />Technical introduction<br />Mechanical overview<br />Hardware architecture<br />Software architecture<br />
  3. 3. USAR Robotics<br />
  4. 4. What is USAR Robotics?<br />Search<br />To look through in a place or in an area carefully in order to find something missing or lost<br />Rescue<br />To free or deliver victim from confinement.<br />USAR: Urban Search And Rescue<br />
  5. 5. What is USAR Robotics?<br />Search<br />To look through in a place or in an area carefully in order to find something missing or lost<br />Rescue<br />To free or deliver victim from confinement.<br />Developing robots to be used in USAR application<br />
  6. 6. Why use robots for USAR?<br />3-D law<br /> Robots can help in Dirty,Dangerous, DullTasks.<br /> They can do what rescuers or rescue dogs can’t!<br />voids smaller than person can enter<br />voids on fire or oxygen depleted<br />Lose ½ cognitive attention with each level of protection<br />Void:1’x2.5’x60’<br />Void on fire<br />
  7. 7. Why use robots for USAR?<br />3-D law<br /> Robots can help in Dirty, Dangerous, DullTasks.<br />The most important person in a rescue attempt is the rescuer!<br />Not enough trained people<br />1 survivor, entombed: 10 rescuers, 4 hours<br />1 survivor, trapped/crushed: 10 rescuers, 10 hours<br />135 rescuers died Mexico City, 65 in confined spaces<br />
  8. 8. Why use robots for USAR?<br />3-D law<br /> Robots can help in Dirty,Dangerous, Dull Tasks.<br /> They save time!<br />Time is very critical<br />Golden 24 hours<br />
  9. 9. Taxonomy of USAR Robots<br />MAV<br />USV<br />Man-packable<br />UAV<br />Man-portable<br />Big-size<br />USAR robots<br />UGV<br />
  10. 10. Brief History of USAR Robotics<br />Oklahoma City bombing (1995)<br /> The Idea of using robots in USAR domain (by R. Murphy andJ. Blitch)<br />Hanshi-Awaji earthquake in Kobe City (1995)<br /> The trigger for theRoboCup Rescueinitiative<br />WTC 9/11 (2001) First practical usage of robots in real USAR application<br />After 2001 rescue robots were applied in several occasions:<br />Boat robots (USV) were used after hurricanes Charley, Dennis, Katrina and Wilma <br />Aerial robots (UAV) were used after earthquake in L’Aquila, Italy<br />0<br />6<br />15<br />
  11. 11. RoboCup Rescue Robot League<br />RoboCup<br />Juniors<br />Seniors<br />Soccer<br />Rescue<br />@Home<br />Soccer<br />Rescue<br />Simulation<br />Simulation<br />Dance<br />Small Size<br />Robot<br />Middle Size<br />Standard Platform<br />Humanoid<br />
  12. 12. RoboCup Rescue Robot League<br />Tasks<br />Finding victims in a simulated destructed building<br />Identifying detected victims (signs of life and identity)<br />Marking victims’ locations on an automatically generated map<br />
  13. 13. RoboCup Rescue Robot League<br />Test Arena<br />Yellow<br />Ramps<br />Autonomous Robots Only<br />Orange<br />Steep Ramp<br />Stairs<br />Red<br />Step-Field<br />Radio Drop-Out<br />Autonomous Mobility<br />
  14. 14. AriAnA Rescue Robot Team<br />
  15. 15. Brief History<br />Start (2005)<br /> • Research phase in Shahed Research Center (2005)<br />Becoming official team of IAUCTB (2006)<br /> • 7th place in final ranking of RoboCup Rescue (2006)<br />Joining with AVA – Malaysia (2008)<br /> • 2nd place in ISME 2008 student projects (2008)<br /> • 7th place in RoboCup Rescue (2009)<br /> • 1st place in Khwarizmi Robotics Competitions (2010)<br />2009<br />2006<br />2007<br />2008<br />2009<br />2010<br />AVA - Malaysia (ISOP Int. Co.)<br />
  16. 16. Mechanical Overview<br />Mobile manipulation in rough terrain:<br />Locomotion<br />Manipulation <br />
  17. 17. Locomotion<br />Mobility as a problem:<br />Rescue robots should be highly mobile.<br />Compromising between Mobility and Complexity of locomotion systems is inevitable.<br />Biomimicry has not yet been a suitable solution due to technical limitations:<br />Nature does not create efficient locomotion systems (living beings must do numerous things).<br />Intelligent control of advanced mobility robots is computationally power hungry. <br />Mobility<br />Complexity<br />Efficiency<br />Various Platforms<br />(for variety of terrains)<br />Complexity<br />as less complicated as possible to fulfill a task<br />
  18. 18. Hybrid Locomotion<br />Our solution:<br />Designing a walking mechanism which is not necessarily inspired from the nature.<br />Legged systems are very hard to control!<br />Decreasing complexity of control system by means of semi-active joint controlling<br />Triangular Tracked Wheel<br />Legged<br />Wheeled<br />Tracked<br />Higher maneuverability<br />on rough terrains<br />Higher traction +<br />Lower ground pressure<br />Higher efficiency<br />while steering<br />
  19. 19. Concept of TTW Mechanism<br />2 DOF:<br />Tracks (velocity & torque controlled)<br />Triangular frames (semi-active joint):<br />Active (position, velocity & torque controlled)<br />Passive<br />
  20. 20. Concept of TTW Mechanism<br />Active joint controlling:<br />Continuous movement:<br /> Tracks traveling -> suitable for flat grounds <br />(This type is also available in passive mode)<br />Discrete movement:<br />Triangular frames rotation -> for rough terrains<br />Combined movement:<br /> Both tracks and triangles -> for ultra-rough terrains<br />
  21. 21. Concept of TTW Mechanism<br />Passive joint controlling: <br />Surface adaptation:<br />Lateral adaptation: Increasing traction without control process<br />Axial adaptation:Passing obstacles without control process<br />Not actually controlled but is monitored!<br />
  22. 22. Manipulator<br />Manipulator:<br />Surveillance<br />Camera <br />Victim detection sensors<br />Manipulation<br />Camera<br />Victim detection sensors<br />Gripper<br />Problems:<br />DOF:<br />Maneuverability<br />Complexity<br />Accuracy<br />Payload<br />End effector’s orientation correction mechanism: <br />Combination of two parallelogram four-bar linkage with flexible links<br />
  23. 23. Hardware Architecture<br />Power Management System<br />Main Board<br />Communication System<br />Motors & Drivers<br />Video System<br />Sensors<br />
  24. 24. Power Management System<br />Web based PMS:<br />Power distribution<br />Monitoring (voltage & current) <br />Web Interfaced<br />Intelligent control<br />Self-health check<br />
  25. 25. Main Board<br />Industry grade Motherboard<br />Small (115 x 165 mm) <br />Powerful<br />Pentium M 1.4 GHz, 2M L2 cache<br />Robust<br />Fanless (-40 to +80 C)<br />Compact Flash compatible<br />PC/104-plus compatible<br /> 0% ~ 90% relative humidity <br />
  26. 26. Communications<br />Internal<br />Wired<br />External <br />Wireless Communication<br />5 GHz IEEE802.11a Access Point / Bridge<br />
  27. 27. Motors & Drivers<br />High efficiency brushless DC motors <br />~ 90% efficient<br />120 – 200W nominal power<br />Highly efficient Gearhead<br />~ 80% efficient<br />Incremental Encoder<br />1500 cpr<br />Driver<br />Torque control<br />Velocity control<br />Position control<br />
  28. 28. Video System<br />Camera<br />Miniature cam (QTY = 3)<br />Zoom cam (QTY = 1)<br />Optical zoom<br />Auto/Manual control<br />Video Server<br />Industry grade VS<br />Higher quality <br />Resolution: 720 x 480<br />Frame rate: up to 30 fps<br />Robustness<br />3g shock & 1g vibration<br />
  29. 29. Sensors<br />Navigation<br />Dead reckoning<br />Odometry<br />IMU <br />Range sensors<br />Scanning Laser Range Finder<br />Vision <br />Monocular<br />Stereo<br />Proximity sensors<br />Ultrasonic<br />GPS (Outdoor only)<br />
  30. 30. Sensors<br />Victim identification <br />Temperature<br />Thermal imaging camera<br />Temperature scanner <br />Vision <br />Monocular<br />Breathing<br />CO2 sensor<br />
  31. 31. Software Architecture<br />Robotic Server<br />HRI<br />SLAM<br />
  32. 32. Robotic Server<br />Player (started in 2000)<br />A universal driver for robotics<br />Stage<br />2D multi-robot simulator<br />Gazebo (started in 2003)<br />High-fidelity 3D multi-robot simulator<br />
  33. 33. Player / Stage / Gazebo<br />Gazebo (3D simulation)<br />Stage (2D simulation)<br />Controller<br />(client)<br />Player<br />(server)<br />Controller<br />(client)<br />Controller<br />(client)<br />Player<br />(server)<br />Controller<br />(client)<br />TCP, UDP,<br />Jini, Ice<br />RS232, USB, 1394, TCP, Shared Mem<br />© Brian Gerkey<br />
  34. 34. Human Robot Interaction<br />Easy to understand Graphical User Interface (GUI)<br />Video-centric GUI <br />Popular X-Box controller<br />
  35. 35. SLAM<br />SLAM: Simultaneous Localization And Mapping<br />Generating a map of unknown environment while localizing the mapping system within that map<br />
  36. 36. Navigation and SLAM<br />SLAM<br />Mapping<br />Localization<br />Integrated approaches<br />Active localization<br />Exploration<br />Motion control<br />© Makarenko et al<br />
  37. 37. The SLAM Problem<br />Global map<br />(what robot thinks)<br />Ground truth map<br />(what happens)<br />Local map<br />(what robot sees)<br />Given <br />Robot controls<br />Nearby measurements<br />Estimate<br />Robot state (position, orientation)<br />Map of world features<br />
  38. 38. Structure of SLAM Problem<br />mj<br />Zk,j<br />mi<br />Zk-1,i<br />Xk-1<br />Xk<br />uk<br />
  39. 39. Why SLAM is hard?<br />Chicken and egg problem: robot path and map are both unknown<br />In the real world, the mapping between observations and landmarks is unknown<br />Picking wrong data associations can have catastrophic consequences<br />Pose error correlates data associations<br />Robot pose<br />uncertainty<br />
  40. 40. Questions<br />Thank You!<br />
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