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Temporal Potential Function based Path Planner for Dynamic Environments

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Temporal Potential Function based Path Planner for Dynamic Environments

by Vamsikrishna Gopikrishna

 

08 Dec 2008

Simulates the Temporal Potential Function approach for Path Planning in Dynamic Environments

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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 package, we simulate a such a method for path planning in dynamic environments. The method uses a potential function approach that considers time as a variable when calculating the potential value. This potential value for a particular location and time 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. 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.

MATLAB release MATLAB 7.5 (R2007b)
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Comments and Ratings (5)
28 Jan 2009 Reza

I have problem with pointer in Data Structures and Algorithms Toolbox with the following message:
??? Invalid MEX-file 'C:\...\@POINTER\pointer.dll':
C:\...\@POINTER\pointer.dll is not a valid Win32 application.
How can I solve it?

28 Jan 2009 Vamsikrishna Gopikrishna

You also need to use the pointer library provided at

http://code.google.com/p/pointer/

07 Jun 2009 shanghai ²²

How can I check this algorithm?should I initialize the W and obs matix?I can read clear about your program.while there is on a main function to ord all the functions

14 Jun 2011 Saravana

How can I simulate this program? What r the inputs I need to give? which is the main function?

30 Jan 2012 Patrik Eschle

This *may* be a wonderful path planner. However, it is of no practical use, since the function arguments are not documented.

It is a little effort to describe input and output parameters, add an example and make error messages descriptive. Matlab itself gives the best examples on how to to do this.

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Tag Activity for this File
Tag Applied By Date/Time
artificial intelligence Vamsikrishna Gopikrishna 08 Dec 2008 13:38:33
robotics Vamsikrishna Gopikrishna 08 Dec 2008 13:38:33
path planning Vamsikrishna Gopikrishna 08 Dec 2008 13:38:33
harmonic function Vamsikrishna Gopikrishna 08 Dec 2008 13:38:33
potential function Vamsikrishna Gopikrishna 08 Dec 2008 13:38:33
dynamic environment Vamsikrishna Gopikrishna 08 Dec 2008 13:38:33
simulator Vamsikrishna Gopikrishna 08 Dec 2008 13:38:33
path planning Devlin Messmer 06 May 2009 02:19:13
potential fields Devlin Messmer 06 May 2009 02:19:29
fuzzy logic Devlin Messmer 06 May 2009 02:19:35
potential function Hamad 31 Oct 2011 04:46:03

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