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					                             Autonomous Robots: Frontier Searching
Alex Morales, Computer Science, Joey Durham, Mechanical Engineering, Francesco
                Bullo, Mechanical Engineering UC Santa Barbara

  Introduction/Background                                                Robot and sensor hardware                                   Player/Stage interface
   In searching problems a robot is looking for a target in a                                                                           Player/Stage is an interface which we use to test and
                                                                      The robots we use are Videre ERA-MOBI model. Each              simulate our robot algorithms. Stage simulates mobile robots
potentially unknown domain. To locate the target it is               contains an on board Linux computer and a laser distance
important that the robot traverses the map efficiently.                                                                              in a two dimensional environment. Using Player/Stage is
                                                                     sensor. More details are listed below.                          convenient especially because our algorithms can be tested
   My searching algorithm for locating the stationary target,
focused on creating a frontier between explored and                  Robot specs:                                                    on either the simulated environment or the real robots and
unexplored regions. The robot iteratively chooses the best                                                                           can easily move from one to the other to make
position on the frontier which maximizes frontier coverage.      ● Size: 40cm(L) x 41cm(W) x 15 cm                                   improvements.
                                                                   (H)
                                                                 ● Batteries: 4-5 Hours with normal
                                                                   movement.
                                                                 ● Encoder accuracy: 500 counts/ rev

                                                                 ● Speed: up to 2 m/s

                                                                 ● Capacity 20kg ( 44lbs)




                                                                                                   Laser specs:

                                                                                                   ● Model: Hokuyo URG laser
                                                                                                     Rangefinder
                                                                                                   ● Range: 5 meters

                                                                                                   ● Scan rate: 10 Hz

                                                                                                   ● Resolution 0.36 degrees



                                                                                                                                      This is an example of the simulated environment, with the robot
                                                                                                                                      (red) and a stationary target (blue).




The Algorithm:        The flowchart bellow explains the
                      steps of the searching algorithm.
                                                                 Robot (red dot) gets distance                                                                         The new visibility polygon
                                                                 data from laser rangefinder.                                                                          merges with the old
                                                                                                                                                                       visibility polygon, creating
                                                                 The frontier and the visibility                                                                       a new frontier.
                     Receive laser data                          polygon are created (green
                                                                 area).                                                                                                The robot saves the new
                                                                                                                                                                       position and local frontier.
  Target Found            Check if
                      Target was found


Objective Finished                   Target not found.


                                       Create local              The robot chooses the next best                                                                       As the robot moves to new
                                     visibility Polygon          position to search.                                                                                   positions in the map, it build a
                                                                                                                                                                       position graph, creating a
                                                                  The best position is a point on                                                                      map of the explored region
                                         Update Global
                                                                 the frontier that maximize frontier
                                           Frontier.
                                                                 coverage.


        All frontiers have          Decide next move
         been searched.
                                     Move to position
                                        chosen                                                                                                                         The robot can then use this
                                                                     Once at new position, the                                                                         position graph to navigate the
            No Target                                                robot again constructs a                                                                          environment and checking for
       In the environment.                                           visibility polygon.                                                                               shortest distances to
                                                                                                                                                                       unexplored regions of the
                                                                                                                                                                       environment.
        Finished searching




    Properties of Algorithm                                                         Efficiency                                              Future Research
                                                                                                                                           This algorithm is also a foundation for solving
     This search algorithm is complete meaning that it will        By weighting the best next position based on the lengths of the
                                                                                                                                         more complex variation on this search problem. For
 find a target when one exists, or determine there is no        frontier segments covered, we believe that the algorithm
 target after exploring the entire environment. This claim      maximizes the expected exposure of unexplored area. By max               example, this algorithm can be extended to multiple
 holds with appropriate assumptions on the topology of the      exposure on each iteration the algorithm minimizes the expected          searchers or a moving target.
 environment.                                                   time to detection.

    Some of the limitations on the algorithm could come            In addition, depth-first traversal of the position graph helps
 from the accuracy of the sensor data, and the problem of       minimize worst-case time by relating the amount of time the robot
 odometry could effect how the robot navigates the              spends traversing already explored regions.
 environment




 Acknowledgements:
 Fancesco Bullo, Joey Durham,
 UCLEAD coordinators and sponsors

 References:
 Some images found
 on Google Images.

				
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posted:1/9/2013
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