Feedback Control of an Omnidirectional Autonomous Platform for Mobile Service Robots
Journal of Intelligent and Robotic Systems
GA-based Fuzzy System Design in FPGA for an Omni-directional Mobile Robot
Journal of Intelligent and Robotic Systems
Prediction of geometric errors of robot manipulators with Particle Swarm Optimisation method
Robotics and Autonomous Systems
Evolutionary computing based mobile robot localization
Engineering Applications of Artificial Intelligence
Short and long-range visual navigation using warped panoramic images
Robotics and Autonomous Systems
Omni-directional mobile robot controller based on trajectory linearization
Robotics and Autonomous Systems
Fuzzy logic-based real-time robot navigation in unknown environment with dead ends
Robotics and Autonomous Systems
Fuzzy logic techniques for navigation of several mobile robots
Applied Soft Computing
Hybrid intelligent vision-based car-like vehicle backing systems design
Expert Systems with Applications: An International Journal
Intelligent mobile manipulator navigation using adaptive neuro-fuzzy systems
Information Sciences: an International Journal
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Target tracking for mobile robot platforms via object matching and background anti-matching
Robotics and Autonomous Systems
Fuzzy embedded mobile robot systems design through the evolutionary PSO learning algorithm
WSEAS TRANSACTIONS on SYSTEMS
Mobile robot map building from time-of-flight camera
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
An evolutional particle swarm optimization (PSO)-learning algorithm is proposed to automatically generate fuzzy decision rules. Due to the development of the fuzzy rule-based system, it actually regulates the omni-directional vision-based mobile robot for obstacle avoidance and desired target approximation as soon as possible. In the proposed image processing algorithm, an image direct transformation method is applied to convert the omni-directional scene into panoramic normal-view. Thus, the objects positions of obstacle and target are detected by the proposed color image segmentation. Human knowledge-based fuzzy systems demonstrate their well adaptability for nonlinear and time-variant features of the mobile robot to actually approach the desired location whatever it is surrounded in a known or unknown environment. In software simulations, the omni-directional mobile robot can move toward desired targets from different initial positions and various block sizes. In hardware implementations, the fuzzy control system embedded in actual mobile robot platform is used to real-time manipulate the omni-directional wheels through the motor drivers by the captured image positions of the obstacle and target. The selected fuzzy rules are efficient to control the direction and speed of omni-directional wheels to achieve the desired targets.