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Part II Chapter 9: Topological Path Planning

Part II Chapter 9: Topological Path Planning. Objectives. Define the difference between natural and artificial landmarks; give one example of each

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Part II Chapter 9: Topological Path Planning

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  1. Part II Chapter 9:Topological Path Planning Chapter 9: Topological Path Planning

  2. Objectives • Define the difference between natural and artificial landmarks; give one example of each • Given a description of an indoor office environment and a set of behaviors, build a relational graph representation labeling the distinctive places and local control strategies for gateways • Describe in one or two sentences: gateway, image signature, visual homing, viewframe, orientation region • Given a figure showing landmarks, create a topological map showing landmarks, landmark pair boundaries, and orientation regions Chapter 9: Topological Path Planning

  3. Behaviors Behaviors Behaviors Behaviors Navigation • Where am I going? Mission planning • What’s the best way there? Path planning • Where have I been? Map making • Where am I? Localization Carto- grapher Mission Planner deliberative How am I going to get there? reactive Chapter 9: Topological Path Planning

  4. Spatial Memory • What’s the Best Way There? depends on the representation of the world • A robot’s world representation and how it is maintained over time is its spatial memory • Attention • Reasoning • Path planning • Information collection • Two forms • Route (or qualitative) • Layout (or metric) • Layout leads to Route, but not the other way Chapter 9: Topological Path Planning

  5. Route, or Qualitative Navigation Two categories Relational spatial memory is a relational graph, also known as a topological map use graph theory to plan paths Associative spatial memory is a series of remembered viewpoints, where each viewpoint is labeled with a location good for retracing steps

  6. Topological Maps Use Landmarks • A landmark is one or more perceptually distinctive features of interest on an object or locale of interest • Natural landmark: configuration of existing features that wasn’t put in the environment to aid with the robot’s navigation (ex. gas station on the corner) • Artificial landmark: set of features added to the environment to support navigation (ex. highway sign) • Roboticists avoid artificial landmarks! Chapter 9: Topological Path Planning

  7. Desirable Characteristics of Landmarks • Recognizable (can see it when you need to) • Passive • Perceivable over the entire range of where the robot might need to view it • Distinctive features should be globally unique, or at least locally unique • Perceivable for the task (can extract what you need from it) • ex. can extract relative orientation and depth • ex. unambiguously points the way • Be perceivable from many different viewpoints Chapter 9: Topological Path Planning

  8. Example Landmarks Chapter 9: Topological Path Planning

  9. floor plan Gateway is an opportunity to change path heading relational graph Relational Methods Nodes: landmarks, gateways, goal locations Edges: navigable path

  10. Problems with early relational graphs • Not coupled with how the robot would get there • Shaft encoder uncertainty accumulates Chapter 9: Topological Path Planning

  11. Kuipers and Byun: Spatial Hierarchy Chapter 9: Topological Path Planning

  12. Distinctive Place Approach Local control strategies (behaviors to get robot between DPs) Distinctive Places (recognizable, & at least locally unique) Chapter 9: Topological Path Planning

  13. neighborhood boundary distinctive place (within the corner) path of robot as it moves into neighborhood and to the distinctive place Actually Getting to a Distinctive Place: Neighborhoods Use one behavior until sees the DP (exteroceptive cueing) then swap to a landmark localization behavior

  14. de3 r1 r2 fh mtd mtd Room 1 Room 2 t1 fh t2 fh t3 fh de1 mtd mtd fh r4 r3 Room 3 Room 4 de2 Class Exercise • Create a relational graph for this floorplan • Label each edge with the appropriate LCS: mtd, fh • Label each node with the type of gateway: de, t, r Chapter 9: Topological Path Planning

  15. Case Study • Representation • Sequencing of behaviors based on current perception (releasers) and subgoal • Algorithm Chapter 9: Topological Path Planning

  16. Hd nodes because Have different perception R3->R7 Chapter 9: Topological Path Planning

  17. Transition Table Chapter 9: Topological Path Planning

  18. Path Planning Algorithm • Relational graph, so any single source shortest path algorithm will work (Dijkstra’s) • If wanted to visit all rooms, what algorithm would you use? Chapter 9: Topological Path Planning

  19. Execution Exception subscript Chapter 9: Topological Path Planning

  20. Associative Methods • Visual Homing • bees navigate to their hive by a series of image signatures which are locally distinctive (neighborhood) • QualNav • the world can be divided into orientation regions (neighborhoods) based on perceptual events caused by landmark pair boundaries • Assumes perceptual stability, perceptual distinguishability Randal Nelson, URochester Daryl Lawton, Advanced Decision Systems Chapter 9: Topological Path Planning

  21. Image Signatures The world Tesselated (like faceted-eyes) Resulting signature for home Chapter 9: Topological Path Planning

  22. Move to match the template Chapter 9: Topological Path Planning

  23. OR2 OR1 Topological Representation as Orientation Regions mountain Metric Map building radio tower tree

  24. Summary • Route, qualitative, and topological navigation all refer to navigating by detecting and responding to landmarks. • Landmarks may be natural or artificial; roboticists prefer natural but may have to use artificial to compensate for robot sensors • There are two type of qualitative navigation: relational and associative Chapter 9: Topological Path Planning

  25. Summary (cont.) • Relational methods use graphs (good for planning) and landmarks • The best known relational method is distinctive places • Distinctive places are often gateways • Local control strategies are behaviors • Associative methods remember places as image signature or a viewframe extracted from a signature • can’t really plan a path, just retrace it • direct stimulus-response coupling by matching signature to current perception Chapter 9: Topological Path Planning

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