1 / 40

Chapter 2 : Bug Algorithms

Chapter 2 : Bug Algorithms. Hyoekjae Kwon Sungmin Lee. contents. <Part 1> 1. About Bug 2. Bug1 Algorithms 3. Bug2 Algorithms <Part 2> 4. Tangent Bug Algorithm <Part 3> 5. Implementation 6. Q & A. <Part 1> (Bug1, Bug2). What’s Special About Bugs. Bug 1. Goal. Start.

becky
Download Presentation

Chapter 2 : Bug Algorithms

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Chapter 2 : Bug Algorithms Hyoekjae Kwon Sungmin Lee

  2. contents <Part 1> 1. About Bug 2. Bug1 Algorithms 3. Bug2 Algorithms <Part 2> 4. Tangent Bug Algorithm <Part 3> 5. Implementation 6. Q & A

  3. <Part 1> (Bug1, Bug2)

  4. What’s Special About Bugs

  5. Bug 1 Goal Start

  6. Bug 1 More formally

  7. Bug 1 analysis Goal Start

  8. Bug 2 Goal Start

  9. The Spiral Goal Goal Start Start

  10. Bug 2 More formally

  11. Bug 2 analysis Start Goal

  12. head-to-head comparison Start Goal Goal Start

  13. BUG 1 vs. BUG 2

  14. <Part 2> (Tangent Bug)

  15. The Basic Ideas • A motion-to-goal behavior as long as way is clear or there is a visible obstacle boundary pt that decreases heuristic distance • A boundary following behavior invoked when heuristic distance increases. • A value dminwhich is the shortest distance observed thus far between the sensed boundary of the obstacle and the goal • A value dleavewhich is the shortest distance between any point in the currently sensed environment and the goal • Terminate boundary following behavior when dleave< dmin

  16. Tangent Bug Algorithm Goal Start H : hit point D : depart point M : minimum point L : leave point

  17. Tangent Bug Algorithm • 1) repeat • a) Compute continuous range segments in view • b) Move toward n {T,Oi} that minimizes h(x,n) = d(x,n) + d(n,qgoal) until • a) goal is encountered, or • b) the value of h(x,n) begins to increase • 2) follow boundary continuing in same direction as before repeating a) update {Oi}, dleaveand dmin until • a) goal is reached • b) a complete cycle is performed (goal is unreachable) • c) dleave< dmin

  18. Raw Distance Function Saturated raw distance function

  19. Intervals of Continuity Tangent Bug relies on finding endpoints of finite, continued segments of ρR

  20. Motion-to-Goal Transitionfrom Moving Toward goal to “following obstacles” Currently, the motion-to-goal behavior “thinks” the robot can get to the goal

  21. Transition from Motion-to-Goal

  22. Motion To Goal Example

  23. Motion To Goal Example

  24. Minimize Heuristic Example At x, robot knows only what it sees and where the goal is, so moves toward O2. Note the line connectingO2 and goal pass through obstacle so moves toward O4. Note some “thinking” was involved and the line connectingO4 and goal pass through obstacle For any Oi such that d(Oi,qgoal) < d(x,qgoal), choose the part Oithat minimizes d(x,Oi) + d(Oi,qgoal)

  25. dminand dleave • A value dminwhich is the shortest distance observed thus far between the sensed boundary of the obstacle and the goal • A value dleavewhich is the shortest distance between any point in the currently sensed environment and the goal

  26. Example: Zero Sensor Range H : hit point D : depart point M : minimum point L : leave point

  27. Example: Finite Sensor Range Goal Start H : hit point D : depart point M : minimum point L : leave point H : hit point D : depart point M : minimum point L : leave point

  28. Example: Infinite Sensor Range Start Goal There is no boundary-following

  29. dminis constantly updated Goal Start

  30. <Part 3> (Implementation)

  31. What Information: The Tangent Line safe distance The dashed line represents the tangent to the offset curve at x.

  32. How to Process Sensor Information The dashed line is the actual path, but the robot follows the thin black lines, predicting and correcting along the path. The black circles are samples along the path.

  33. Sensors

  34. Tactile sensors • Tactile sensors are employed wherever interactions between a contact surface and the environment are to be measured and registered. A tactile sensor is a device which receives and responds to a signal or stimulus having to do with force. <daVinci medical system>

  35. Ultrasonic sensors • Ultrasonic sensors generate high frequency sound waves and evaluate the echo which is received back by the sensor. Sensors calculate the time interval between sending the signal and receiving the echo to determine the distance to an object.

  36. Polaroid ultrasonic transducer The disk on the right is the standard Polaroid ultrasonic transducer found on many mobile robots; the circuitry on the left drives the transducer.

  37. Beam pattern for the Polaroid transducer. This obstacle can be located anywhere along the angular spread of the sonar sensor's beam pattern. Therefore, the distance information that sonars provide is fairly accurate in depth, but not in azimuth.

  38. Centerline model The beam pattern can be approximated with a cone. For the commonly used Polaroid transducer, the arc base is 22.5degrees

  39. Reference http://blog.daum.net/pg365/115 http://www.cs.cmu.edu/~motionplanning/student_gallery/2006/st/hw2pub.htm HowieChoset with slides from G.D. Hager and Z. Dodds (Bug Algorithms) Book : Principles of Robot Motion

  40. Question & Answer

More Related