Temporal Potential Function Approach For Path Planning In Dynamic Environments

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dc.contributor Gopikrishna , Vamsikrishna en_US
dc.date.accessioned 2009 -09 -16T18 :20 :06Z
dc.date.accessioned 2011 -08 -24T21 :42 :46Z
dc.date.available 2009 -09 -16T18 :20 :06Z
dc.date.available 2011 -08 -24T21 :42 :46Z
dc.date.issued 2009 -09 -16T18 :20 :06Z
dc.date.submitted January 2008 en_US
dc.identifier.uri http : / /hdl .handle .net /10106 /1820
dc.description.abstract A Dynamic environment is one in which either the obstacles or the goal or both are in motion . In most of the current research , robots attempting to navigate in dynamic environments use reactive systems . Although reactive systems have the advantage of fast execution and low overheads , the tradeoff is in performance in terms of the path optimality . Often , the robot ends up tracking the goal , thus following the path taken by the goal , and deviates from this strategy only to avoid a collision with an obstacle it may encounter . In a path planner , the path from the start to the goal is calculated before the robot sets off . This path has to be recalculated if the goal or the obstacles change positions . In the case of a dynamic environment this happens often . One method to compensate for this is to take the velocity of the goal and obstacles into account when planning the path . So instead of following the goal , the robot can estimate where the best position to reach the goal is and plan a path to that location . In this thesis , we propose such a method for path planning in dynamic environments . The proposed method uses a potential function approach that considers time as a variable when calculating the potential value . This potential value of a particular location and time value indicates the probability that a robot will collide with an obstacle , assuming that the robot executes a random walk from that location and that time onwards . Thus the robot plans a path by extrapolating the object's motion using current velocities and by calculating the potential values up to a look -ahead limit that is determined by calculating the minimum path length using connectivity evaluation and then determining the utility of expanding the look -ahead limit beyond the minimum path length . The method is fast , so the path can be re -planned with very little overhead if the initial conditions change at execution time . The thesis will discuss how the potential values are calculated and how a suitable look -ahead limit is decided . Finally the performance of the proposed method is analyzed in a simulated environment . en_US
dc.language.iso EN en_US
dc.publisher Computer Science & Engineering en_US
dc.title Temporal Potential Function Approach For Path Planning In Dynamic Environments en_US
dc.type M .S . en_US

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Temporal Potential Function Approach For Path Planning In Dynamic Environments. Available electronically from http : / /hdl .handle .net /10106 /1820 .

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