Path Planing of Mobile Robot

Topics: Shortest path problem, Dijkstra's algorithm, Robotics Pages: 27 (9175 words) Published: August 25, 2013
A Report
on

PATH PLANNING OF MOBILE ROBOT

By

|Names of the students |ID Nos. |Disciplines | |Rohit Ginoria |2006A4PS228P |B.E. (Hons.)Mechanical Engineering |

Prepared in partial fulfilment of
Lab. Oriented Project
Under the guidance of Dr. B.K.Rout

Birla Institute of Technology and Science, Pilani (October, 2008)

Acknowledgments

Several people have been instrumental in allowing this project to be completed. I am grateful to Dr. B.K.Rout, for giving me opportunity to do this project and for guiding me throughout the project. God, the Almighty you are always a wonderful inspiration to me. ABSTRACT

Abstract – Obstacle avoidance is one of the main concerns of every robot’s trajectory. Planning path algorithm is the important step to avoid obstacle during the motion of autonomous robot. Many algorithms have been implemented and are being worked upon for further improvement. This report deals with some of the important algorithms used in the robot industry. Key Words – Path-planning, robot’s trajectory, obstacle avoidance, TSP, Genetic Algorithm, Vector Potential Field, Visibility Graph

List of tables and Figures
Symbols and abbreviation used

Conclusion
Literature review
References and bibliography

Table of contents

Acknowledgement
Abstract
List of Illustration
1. Introduction
2. Path Planning
1. Configuration Space
2. Road map approach
1. Visibility Graph
2. Voronoi Graph
3. Cell decomposition approach
4. Potential field approach
3. Virtual Force Field
1. The Basic VFF
2. Low Pass Filter for Steering Control
3. Sped Control
4. A-Star Algorithm
1. The Arena
2. Starting the Search
3. Path Scoring
4. Calculations
5. Continuing the Search
6. Working
7. Summary
8. Variable terrain cost
9. Smoother paths
10. Dijkstra's Algorithm
5. Travelling Salesman Problem
1. Genetic Algorithm
2. Transportation Model
3. A sample Code by used in MATHEMATICA
6. AGVs (Application of TSP)

1. Introduction

In the artificial intelligence community planning and reacting are often viewed as contrary approaches or even opposites. In fact, when applied to mobile robots, planning and reacting have a strong complementary. During execution, the robot must react to unforeseen events (e.g. obstacles) in such a way so as to still reach the goal. Suppose that a robot M at a time i has a map Mi and an initial belief sate bi. The robot’s goal is to reach a position p while satisfying some temporal conditions: locg(R) = p; (g≤n). Thus the robot must be at p before the nth step. Although the goal of the robot distinctly physical, the robot can only really sense its belief state; not its physical location, and therefore we map the goal of reaching location p to reaching a belief state bg, corresponding to the belief that locg(R) = p. With this formulation a plan q is nothing more than one or more trajectories form bi to bg if the plan is executed from a world state consistent with both bi and Mi. Completeness of a robot

The robot is complete if and only if, for all possible problems (i.e., initial belief states, maps, and goals), when there exists a trajectory to goal belief state, the system will achieve the goal belief state.

2. Path planning

1. Configuration space
Path planning for manipulator robots and indeed, even for most mobile robots, is formally one in a representation called Configuration space. Suppose that a robot arm has k degree of...
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