International Journal of Advanced Robotic Systems · 2004 · 186 citations · 5 references
Robot KinematicsEngineeringRobot PlanningGlobal PlanningIntelligent RoboticsTrajectory PlanningRobot LearningKinematicsHealth SciencesPath PlanningRobot Motion PlanningMotion SynthesisFirst Neural NetworkComputer ScienceNeural NetworksRobot ControlCellular Neural NetworkMotion PlanningPlanningRobotics
The environment contains arbitrarily shaped, potentially moving obstacles. The study proposes a neural‑network–based motion‑planning approach for autonomous robots to navigate safely in such environments. Two neural networks are employed: one maps ultrasound range‑finder data to free space, the other selects safe directions to construct a collision‑free path. Simulations demonstrate that the proposed method generates viable paths for the robot.
This paper deals with a path planning and intelligent control of an autonomous robot which should move safely in partially structured environment. This environment may involve any number of obstacles of arbitrary shape and size; some of them are allowed to move. We describe our approach to solving the motion-planning problem in mobile robot control using neural networks-based technique. Our method of the construction of a collision-free path for moving robot among obstacles is based on two neural networks. The first neural network is used to determine the “free” space using ultrasound range finder data. The second neural network “finds” a safe direction for the next robot section of the path in the workspace while avoiding the nearest obstacles. Simulation examples of generated path with proposed techniques will be presented.
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Artificial neural networks: a tutorial
Abhishek Jain, Jianchang Mao, Khalid Mohiuddin · Computer · 1996 · 4.9K citations