首页|Researchers from Shaoguan University Report New Studies and Findings in the Area of Robotics [Urban Mobile Robot Routing Using Fast Search Ra ndom Tree Method (Rrt) In Obstacle Environments]
Researchers from Shaoguan University Report New Studies and Findings in the Area of Robotics [Urban Mobile Robot Routing Using Fast Search Ra ndom Tree Method (Rrt) In Obstacle Environments]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Robotics have been published. According to news reporting from Shaoguan, People’s Republic of China, by NewsRx journalists, research stated, “In this paper, the objective of path planning and control systems for robot is multifactorial. The method used for navigation algorithms based on is closed-loop random trees with quick search or CL-RRT.” The news correspondents obtained a quote from the research from Shaoguan Univers ity, “In this algorithm, each robot will grow a tree from its current location t o the target or zone target is developed. The main advantage of this method is t he ability to function in complex environments. For use this method, it is neces sary that the CL-RRT algorithm for robot navigation online, be extended. In onli ne mode, the robot does not have any information about the environment and throu gh its sensors, which detect the environment and the ability to function in envi ronments with obstacles dynamic and could face a new obstacle or the possibility of an obstacle’s dynamic (the other a robot) to change its direction during mot ion. Performance of the design path used with design the controller for robot in an environment with various obstacles is evaluated, and then this design is for a group of robots used. To coordinate among agents and to ensure that there is no conflict between them, there is strategy based on priority assignment and LOS method. The strategy used in a way that ensures that the collision between agen ts does not happen and benefits of the design methods path used to keep. As a re sult of this strategy can be divided into two parts, the first part of the prior itization robots and the second part of the strategy, no conflict robot is in mo tion. In this paper, the problem of forming a group of robots has been investiga ted. In other words, the agents move in the number of agents must be a specific form.”
ShaoguanPeople’s Republic of ChinaAs iaEmerging TechnologiesMachine LearningNano-robotRobotRoboticsShaogu an University
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