Autonomous Vehicle

Autonomous Vehicle

Presented By:

Umer Suleman

Mehreen Zafar

Saima Ashraf

1. Overview

By autonomous robot navigation we mean the ability of a robot to move purposefully and without human intervention in environments that have not been specifically engineered for it. Autonomous navigation requires a number of heterogeneous capabilities including the ability to execute elementary goal-achieving actions, like reaching a given location; to react in real time to unexpected events, like the sudden appearance of an obstacle; to build, use and maintain a map of the environment; to determine the robot's position with respect to this map; to form plans that pursue specific goals or avoid undesired situations; and to adapt to changes in the environment.

A number of different architectures for autonomous robot navigation have been proposed in the last twenty years. These include hierarchical architectures, that partition the robot's functionality into high-level (model and plan) and low-level (sense and execute) layers; behavior-based architectures, that achieve complex behavior by combining several simple behavior-producing units; and hybrid architectures, that combine a layered organization with a behavior-based decomposition of the execution layer. While the use of hybrid architectures is gaining increasing consensus in the field, a number of technological gaps remain. Among these, we emphasize:

	How to design simple behaviors that guarantee robust operation in spite of the limited knowledge available at design time; e.g., designing an obstacle avoidance behavior that is effective in face of unknown obstacle configurations.
	How to coordinate the activity of several, possibly competing behaviors in order to perform a complex task; e.g., coordinating goal-achieving and obstacle avoidance behaviors to reach a target position while avoiding unforeseen obstacles.

We in this project adapted the hybrid approach i.e. after receiving the sensor input

it is interpreted and the information is modeled in the map according to our defined perception then the path planning is done on this perceived map and to react to the environment small fundamental behaviors are executed to workout in the given situation.

2. Objectives:

	Reach destination avoiding stationary and moving obstacles.
	Map-building given the information by the sensors about the environment, which is relevant and synchronous with the other processes.
	Decision making with the help of the map.
	Manipulating the decision in accordance with the micro controller interface.
	To cope with some special unexpected situations.

3. Implementation Tools:

	Visual C++ 6.0
	Borland C++

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