Intelligent Robots

The autonomous robots should be capable of recognition, learning and decision making. Path planning is an important issue in the field of robotics. It is a method to find collision free path from the start location to target location, given an environment consisting of obstacles. The path should be optimized using some reasonable algorithm where the optimization criteria can be time, distance or energy depending on the problem. This research will give an improved and efficient algorithm for robotic path planning that will generate an optimized path.

Path planning in unknown environment is very difficult task since the map of the environment is not certain. Though robots are employed with sensors and global positioning system but due to uncertainty

The challenges in the field of designing of intelligent robots require intelligence at subconscious level.

1.2 Objectives of the Project

The problem of path planning by mobile robot can be formulated in its simplest form as: Let R represents a mobile robot which is free to move in two or three dimensional space V. The space consists of some obstacles O and their positions and geometric characteristics are known to the robot prior. Given a start position S and the target location T, the path planning problem is to generate an appropriate path from S to T without any collision.

This research focuses on the path planning of mobile robot in dynamic environment. Following are the objectives of this research:

i. To develop an improved artificial bee colony algorithm for path planning in dynamic environment. This algorithm is expected to generate an optimal and feasible path from start position to target position and the results are expected to be better than previous work done for static environment [4]. ii. To develop an approach that will optimize the final path efficiently and to utilize this approach in determining the feasible and optimal path using improved artificial bee colony algorithm.

1.3 Significance of the

The path generated by original artificial bee algorithm is not optimized. This approach has incorporated the concept of triangle inequality for optimizing the final path. Earlier algorithms generate optimal path by only considering the cost of generating new node in the path and calculating the estimated cost from the new generated node to the final node. Our algorithm has tried to optimize the final path by removing certain unnecessary nodes from the final path using the technique of triangle inequality.

1.4 Contribution of the Thesis

This research work will provide an efficient framework for determining efficient path for the robot in dynamic environment. The main contributions of the thesis are:

i. The improved artificial bee colony (IABC) algorithm has better performance in static environment as compared to other existing approaches [6, 7, 9]. ii. The framework will provide an efficient method of path planning in dynamic environment. iii. The IABC framework will provide an optimal path planning method in dynamic environment.

1.5 Outline of the Thesis

Chapter 1 introduces the thesis title along with the objectives of the research done, its contribution to the path planning in the field of robotics and the significance of the research work performed.

Chapter 2 deals with the literature reviews about path planning of mobile robot in different environments. It also describes different approaches used for path planning in static and dynamic