Algorithm for Robot Navigation Without Collisions

Algorithm for Robot Navigation Without Collisions ALGORITHM FOR ROBOT NAVIGATION AT ENVIRONMENT WITHOUT COLLISION Â   ALGORITHM REPRESENTATION FOR NAVIGATION OF MOBILE ROBOT WITHOUT OBSTACLE COLLISON Mobile robot It is a kind of robot that has the ability to travel Relative to the environment (i.e. locomotion), and one of the actuators of the robot is the locomotive system This chapter of my bachelor thesis is to develop algorithms that will help the autonomous mobile robot in visual navigation. g the robot. Then, the robot tries to understand their environment to extract data from a sequence of image data, in this case, optical, and then uses this information as a guide for the movement. The strategy adopted to avoid collisions with obstacles during movement – a balance between the right and left optical flow vectors. An integral part of any navigation scheme is the desire to reach a destination and do not get lost or bump into any of the objects. There may be other restrictions on a given route, such as speed limits or zo nes of uncertainty, where in theory, of course, can pave the path, but not desirable. Often, the way is to move the robot autonomously planned, ie on the basis of previous input and without interference in real time. It can work effectively, but only on condition that the environment is perfectly known and does not change and the robot can travel on the route perfectly. However, in the real world everything is much more complicated. Note that navigation will include: Location of robot Environment perception and his model Methods of traffic planning Robot motion control algorithms The problem of mobile robot navigation is a very complex issue characteristic at both ends. The implementation of tasks by moving a mobile robot requires obtaining information about the surrounding-limiting environment – hence the importance of having AD sensory system that allows the observation of the environment and its perception, For this purpose, both simple rangefinder systems and co ntact sensors, which correspond with collision detection. Using a constant speed of 4m/s for the algorithm and a step size of 0.125m which was obtained by the multiplication of the speed by interval in which information is received. = 0.125m. The algorithm is given below. Set iteration values K equals K =1. Tolerance factor ÃŽ ´ Using the following sequence inside the loop for K Evaluating Hessian and the gradient and also checking for positive definite of hessian matric Determine Newton Direction Normalize Newton Direction Determine step size Determine new point If || ΔT||< ÃŽ ´, if not set K=1 And repeat step 2.otherwise terminate But considering the above algorithm it’s still going to encounter some problems. For example saw tooth pattern that occurs at the along the path, shown below: Saw-tooth pattern Saw-tooth happens due to fixed step size at some point in the navigation of the mobile robot reduction in step size is necessary which also means reduction in the speed of the robot . The reason for this effect is because the present point of the robot is not always the best point possible. Meaning that point after that will guide the path back, resulting in a saw=tooth pattern zig -zagging along the path. The reason this problem occurs is because the robot has a constant speed.