Publication | Closed Access
Mobile Robot Navigation Control in Moving Obstacle Environment Using Genetic Algorithm, Artificial Neural Networks and A* Algorithm
53
Citations
12
References
2009
Year
Unknown Venue
EngineeringField RoboticsIntelligent RoboticsTrajectory PlanningGenetic AlgorithmSystems EngineeringKinematicsObstacle EnvironmentMultirobot SystemPath PlanningIntelligent OptimizationDistributed RoboticsComputer EngineeringComputer ScienceAutonomous NavigationRobot TravelArtificial Neural NetworksAutomationCollision Free MovementRobotics
The pace of development and automation urge the need of robots controlling much of the work which used to be done mainly by humans. The modern technology has emphasized on the need to move a robot in an environment which is dynamically changing. An example of such an application may be the use of robots in industry to carry tools and other materials from one place to other. Since many robots would be working together, we need to ensure a collision free navigation plan for each of the robots.In this paper we find out the nearly most optimal path of the robot using Genetic, ANN and A* algorithms at each instant of time of robot travel. It may be used by the industry to send robots for surveys, data acquisition, doing specific work etc. The collision free movement of robot in a moving obstacle environment can be used to move robot in a world of robots.Results show that all 3 algorithms are able to move the robot without any collisions.
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