Скачать презентацию The Office Marathon Robust Navigation in an Indoor Скачать презентацию The Office Marathon Robust Navigation in an Indoor

920ab76e3cff7cf82b832b1aa8512795.ppt

  • Количество слайдов: 18

The Office Marathon: Robust Navigation in an Indoor Office Environment Marder-Eppstein, Eitan, Berger Eric, The Office Marathon: Robust Navigation in an Indoor Office Environment Marder-Eppstein, Eitan, Berger Eric, Foote Tully, Gerkey Brian P. , and Konolige Kurt International Conference on Robotics and Automation, 2010 Zhou Xin 2011. 5. 13

The authors come from… • Willow Garage, Inc. – http: //www. willowgarage. com • The authors come from… • Willow Garage, Inc. – http: //www. willowgarage. com • working on – – – – Perception Motion planning Navigation Hardware integration Simulation Visualizers And more…

Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion

Problem Description – Reachable goal – Unmodified office-like environment – Autonomous navigation – Avoiding Problem Description – Reachable goal – Unmodified office-like environment – Autonomous navigation – Avoiding obstacles • Robot can’t step over – 3 D Obstacles • Can change location

Problem Description • Rounding a blind corner • Cluttered environment -Unknown space -Various obstacles Problem Description • Rounding a blind corner • Cluttered environment -Unknown space -Various obstacles

Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion

Key Challenge • Detecting and Avoiding • The non-trivial 3 D structure obstacles Key Challenge • Detecting and Avoiding • The non-trivial 3 D structure obstacles

Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion

Platform • 8 -wheeled omni-directional base • 2 Laser scanner • ROS(Robot Operation System) Platform • 8 -wheeled omni-directional base • 2 Laser scanner • ROS(Robot Operation System)

Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion

Approach • A. Sensor Processing Pipeline – Sensor is imperfect – Accuracy: 1. 5 Approach • A. Sensor Processing Pipeline – Sensor is imperfect – Accuracy: 1. 5 cm – Random SAmple Consensus (RANSAC[1] ) algorithm

Approach • Core—Voxel Grid – Each cell in Grid • Occupied • Free • Approach • Core—Voxel Grid – Each cell in Grid • Occupied • Free • Unknown – Two dimensional array of 32 -bit – Operations • Marking • Clearing(Bresenham[2])

Approach -- Policy • Entrapment – In-place rotation – Clear obstacles • Recharging – Approach -- Policy • Entrapment – In-place rotation – Clear obstacles • Recharging – Email a plug-in and unplug request.

Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion

Experimental Results Table 1. Results for the experiment environments both in simulation and the Experimental Results Table 1. Results for the experiment environments both in simulation and the real world

Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion Outline • • • Problem Description Key Challenge Platform Approach Experimental Results Conclusion

Conclusion • A robust navigation system is proposed • Use efficient Voxel-based 3 D Conclusion • A robust navigation system is proposed • Use efficient Voxel-based 3 D mapping • Limitation: – Can not fully get rid of FALSE NEGATIVES. – Can’t detecting when it is stuck.

REFERENCES • • [1] M. Fischler and R. Bolles, “Random Sample Consensus: A Paradigm REFERENCES • • [1] M. Fischler and R. Bolles, “Random Sample Consensus: A Paradigm for Model Fitting with Application to Image Analysis and Automated Cartography, ” Communications of the ACM, vol. 24, pp. 381– 395, 1981. [2] J. Bresenham, “Algorithm for computer control of a digital plotter, ” IBM Systems J. , vol. 4, no. 1, pp. 25– 30, 1965.