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نوع فایل : .PPT ( قابل ويرايش و آماده پرينت )
قسمتی از متن .PPT :
تعداد اسلاید : 20 اسلاید
Using Genetic Algorithms
BY: Fatemeh Dehghan
Mona Yaghoubi
ADVISOR :Dr Toosizadeh ROBOTICS This Presentation Introduction
Genetic Algorithm
Problem Formulation
Proposed Path Planning Algorithm
Result
conclusions Introduction Goal:
find the optimal path for a mobile robot to move in a static environment expressed by a map with nodes and links.
Using :
genetic algorithm
Binary code
Fixed length chromosome

ASSUMEPTION
the robot passes each point only once or not at all.

Introduction PATH PLANNING Identification:
given, plan a collision-free path between two specified points in satisfying an optimization criterion with constraints (most commonly: shortest path).

Application
exhibitions, museums, laboratories to transport materials.

Many methods have been reported to generate an optimal path such dynamic programming,
Fuzzy Logic ,
Soft computing ,
Genetic Algorithm (Recently),
… model-based
priori models of known obstacles are used to generate a collision free-path

sensor based
detect and avoid unknown obstacles (dynamic environment).
path planning classify Genetic Algorithm A genetic algorithm maintains a population of candidate solutions, where each candidate solution is usually coded as binary string called a
chromosome.
Coding : Binary , String , Number ,…
Initial
Generation
Fitness Evaluation < ,then Rank , >
Selection
Reproduction

Stop:
an acceptable solution is found,
convergence criterions met
a predetermined limit number of iteration is reached.
Problem Formulation Goal: plan a collision-free optimal path between the starting point and the goal point.
Optimization goals :
1) Minimize distance traveled (shortest path)
2) Maintain a smooth trajectory
3) Satisfy the clearance requirements
(the robot should not approach
the obstacles too closely)


This article:shortest path

Proposed Path Planning Algorithm
Static environment : a map with nodes (via points)and links.

Initial population: random,include admissible or un-admisible.


Assume: a path planning the robot passes each point only once or not at all.








Example Example path :

0-4-5-10-9-15


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