Czasopismo | ELEKTRONIKA - KONSTRUKCJE, TECHNOLOGIE, ZASTOSOWANIA | Rocznik 2013 - zeszyt 12

Real-time pathfinding algorithms in practical application

nr katalogowy: 81419

Modern mobile robots can perform a variety of tasks spanning from simple movement to highly sophisticated environment map creation [1]. The overall performance is greatly influenced by the hardware installed. For that reason, engineers aim to develop CP Us with high processing power and low energy consumption, as well as high amount of memory available for storing program data. Such approach allows for creation of smaller and lighter constructions with longer operation time. Unfortunately, there is a limit of how much can be achieved with hardware alone. The importance of using the right software can be clearly seen in the time a robot needs to find the shortest available route between two points [2]. To this end, researchers are developing more efficient algorithms for finding the optimal path. The main goal of the robot is to calculate the best way from the starting to the ending points with as low cost as possible. There are many path finding algorithms, each of them exhibiting different advantages and disadvantages. Among them there is the Lee's algorithm [7], which is an application of the breadthfirst shortest path search algorithm. Unfortunately, it is highly inefficient because it requires vast amounts of memory and slows down with bigger maps. There are many variations of the original Lee’s algorithm [8]. Other algorithms that present good results are the fluid motion algorithm [9] and the motor schema based algorithm [10]. The first represents the approach of fluid’s reaction to obstacles, dynamically adjusting to the environment and the second combines multiple schemas into an efficient decision making pathfinder. Another algorithm that can be effective is called Ant Colony Optimization (ACO ) [11]. It originated from observation of ants' pathfinding abilities and is said to produce optimal path in finite time. The algorithm depends on the quality of solution from multiple simulation agents ([...]

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