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All Journal IAES International Journal of Robotics and Automation (IJRA)
Zhou Feng
Shandong Institute of Commerce And Technology
Automotive Engineering Electrical & Electronics Engineering

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A Novel Path Planning for Robots Based on Rapidly-Exploring Random Tree and Particle Swarm Optimizer Algorithm Zhou Feng
IAES International Journal of Robotics and Automation (IJRA) Vol 3, No 2: June 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (165.828 KB) | DOI: 10.11591/ijra.v3i2.pp107-111

Abstract

A based on Rapidly-exploring Random Tree(RRT) and Particle Swarm Optimizer (PSO) for path planning of the robot is proposed.First the grid method is built to describe the working space of the mobile robot,then the Rapidly-exploring Random Tree algorithm is used to obtain the global navigation path,and the Particle Swarm Optimizer algorithm is adopted to get the better path.Computer experiment results demonstrate that this novel algorithm can plan an optimal path rapidly in a cluttered environment.The successful obstacle avoidance is achieved,and the model is robust and performs reliably.
Rolling Path Plan of Mobile Robot Based on Automatic Diffluent Ant Algorithm Zhou Feng
IAES International Journal of Robotics and Automation (IJRA) Vol 3, No 2: June 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (246.489 KB) | DOI: 10.11591/ijra.v3i2.pp112-117

Abstract

This paper proposes a new rolling algorithm for path plan of mobile robot based on automatically shunt the ant algorithm.The goal node is mapped to the node nearby the boundary in the eyeshot of the robot, and make out the best partial path, which the robot goes ahead for a step. The algorithm will iterate one time when the robot arrives at the goal node. The robot will reach the destination along the optimal path. Simulation experiments illustrate that the algorithm can be used to plan the optimal path for mobile robot even in the complex and unknown static environment.
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