Navigation of mobile robots using artificial intelligence technique.

The ability to acquire a representation of the spatial environment and the ability to localize within it are essential for successful navigation in a-priori unknown environments. This document presents a computer vision method and related algorithms for the navigation of a robot in a static environment. Our environment is a simple white colored area with black obstacles and robot (with some identification mark-a circle and a rectangle of orange color which helps in giving it a direction) present over it. This environment is grabbed in a camera which sends image to the desktop using data cable. The image is then converted to the binary format from jpeg format using software which is then processed in the computer using MATLAB. The data acquired from the program is then used as an input for another program which controls the robot drive motors using wireless controls. Robot then tries to reach its destination avoiding obstacles in its path. The algorithm presented in this paper uses the distance transform methodology to generate paths for the robot to execute. This paper describes an algorithm for approximately finding the fastest route for a vehicle to travel one point to a destination point in a digital plain map, avoiding obstacles along the way. In our experimental setup the camera used is a SONY HANDYCAM. This camera grabs the image and specifies the location of the robot (starting point) in the plain and its destination point. The destination point used in our experimental setup is a table tennis ball, but it can be any other entity like a single person, a combat unit or a vehicle

Controling of Mobile Agents using Intelligent Strategy

Robots are developed to carry out certain task to help the human beings. A robot carrying out a particular needed task has promising applications for the betterment of human society. So the control of their motion remains a vital part for a robot. In this project, I have to develop the simulation of mobile agents (robots) in an arena of obstacles from a start point to a destination point without collision. So in a way this project deals with successful navigation of robots in prior known environment. This document presents a computer vision method and related algorithms for the navigation of a robot in a static environment. Our environment is a simple white coloured area with coloured obstacles (circle with white colour, rectangles with orange colour, triangle with green colour and hexagon with pink colour which helps in identifying the obstacle) and robot is in a rectangular form. The agents starting point is in blue colour and the destination point is in red colour. This environment is input by the user with the starting point and the destination point. The data acquired from here is then used as an input for the program which controls the robot drive motion in graphic control window. Robot then tries to reach its destination avoiding obstacles in its path. The algorithm presented in this paper uses the distance transform methodology to generate paths for the robot to execute which are written in C++ compiler. These paper developments can also be applied to vehicles for collision free driving

Collision Avoidance for UAVs Using Optic Flow Measurement with Line of Sight Rate Equalization and Looming

A series of simplified scenarios is investigated whereby an optical flow balancing guidance law is used to avoid obstacles by steering an air vehicle between fixed objects/obstacles. These obstacles are registered as specific points that can be representative of features in a scene. The obstacles appear in the field of view of a single forward looking camera. First a 2-D analysis is presented where the rate of the line of sight from the vehicle to each of the obstacles to be avoided is measured. The analysis proceeds by initially using no field of view (FOV) limitations, then applying FOV restrictions, and adding features or obstacles in the scene. These analyses show that using a guidance law that equalizes the line of sight rates with no FOV limitations, actually results in the vehicle being steered into one of the objects for all initial conditions. The research next develops an obstacle avoidance strategy based on equilibrating the optic flow generated by the obstacles and presents an analysis that leads to a different conclusion in which balancing the optic flows does avoid the obstacles. The paper then describes a set of guidance methods that with real FOV limitations create a favorable result. Finally, the looming of an object in the camera\u27s FOV can be measured and used for synthesizing a collision avoidance guidance law. For the simple 2-D case, looming is quantified as an increase in LOS between two features on a wall in front of the air vehicle. The 2-D guidance law for equalizing the optic flow and looming detection is then extended into the 3-D case. Then a set of 3-D scenarios are further explored using a decoupled two channel approach. In addition, a comparison of two image segmentation techniques that are used to find optic flow vectors is presented

Optimum flight trajectories for terrain collision avoidance

Ground Proximity Warning Systems (GPWS), Enhanced Ground Proximity Warning Sensors (EGPWS) and Terrain Awareness Systems (TAWS) have been developed to aid in the reduction of aircraft ground collisions. They are devices which provide pilots with an aural warning signal of proximity of terrain. These systems make use of a downward looking sensor which senses the proximity of oncoming terrain. Certainly these warning devices are beneficial if the pilot reacts to them but they do not assist in improving the situation awareness of the flight crew or what action to take to avoid a collision. The implementation of such systems has reduced aircraft accidents caused by Controlled Flight into Terrain (CFIT) however it has not been eliminated. Thus it is necessary for a new system to be developed, that would not only act like a warning, but would also be capable of assisting the pilot by providing him with safe escape trajectories in a situation which could eventuate into a CAT accident. Pilots usually conduct a pull- up manoeuvre when in ground proximity to increase altitude. This is a logical response but in high mountainous terrain, this manoeuvre may still result in a collision. Furthermore, the sudden pull up manoeuvre could cause the aircraft to exceed its aerodynamics, structural and propulsion limitations. For example load factor. Hence, the primary aim of this research is to develop a methodology utilizing the availability of a three dimensional digital terrain topology database and aircraft position to compute safe escape trajectories in both vertical and lateral directions. The aircraft model used was a Phantom F4. The objective of this thesis is to prove that flying around a terrain can provide the pilot a better chance of survival than by conducting the regular pull up manoeuvre in case there is not adequate time. To add more value to this study, two more objective functions have been added, minimum time and minimum clearance from the terrain. In the former case, the aircraft has to clear the terrain in the least possible time whilst in the latter case; the aircraft has to clear the terrain by flying close to the terrain at a specified clearance. The two scenarios have been selected as military aircraft are most often involved in Terrain Avoidance (TA) and Terrain Following (TF) operations to prevent them from being exposed to enemy fire. However emphasis is given more on avoiding collision rather than planning a collision avoidance strategy. The second part of this investigation involves a sensitivity analysis of instrument errors on the ability to fly an optimal escape trajectory. Instrumental errors are always present and should be considered in any flight simulation to determine how practical the methodology is. To investigate the extent of influence of instrumental errors, there is a need to conduct a sensitivity analysis which is presented. The sensitivity study involves consideration of various scenarios in which the aircraft is required to fly an optimal flight trajectory out of collision. The principal reason for such analysis Is to determine the sensitivity of the optimal escape trajectory solution subjected to instrument errors. Snopt and Direct software were used extensively in Matlab environment version 7 for all the analytical work conducted for this thesis. The three dimensional terrains were initially generated via using functions such as cylinders, cones, etc. Subsequently the more complicated shape of the terrains were generated in Terrain Generator which was exported and converted to Direct format file using B-Splines function in Matlab. Further details pertaining to generation of results are provided. The results obtained in this thesis show that generation of safe aircraft trajectories in a three dimensional digital terrain topology are possible. Although the equations of motion were based on three degrees of freedom, there were limitations added on the dynamics of the aircraft to make it realistic. The ability to use different terrains for modelling also proves that the method is versatile. Finally investigation of the sensitivity analysis shows the ability to counter act the errors in navigational instruments of the aircraft