首页|Research Study Findings from University of Technology Update Understanding of Ro botics (Kinematic and Dynamic Modeling Based on Trajectory Tracking Control of M obile Robot with Mecanum Wheels)
Research Study Findings from University of Technology Update Understanding of Ro botics (Kinematic and Dynamic Modeling Based on Trajectory Tracking Control of M obile Robot with Mecanum Wheels)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in robotics. According to news reporting out of Baghdad, Iraq, by NewsRx editors, r esearch stated, "The trajectory tracking is important to make the WMR move auton omously from the starting point to the destination along a predefined time. Impl ementing of trajectory tracking control is a fundamental part to accomplish its application tasks." The news journalists obtained a quote from the research from University of Techn ology: "In this article a new method by using a hybrid controller has been prese nted to solve the problem of the trajectory tracking of four mecanum wheeled mob ile robot. Proposed controller is depending on modeling of robot kinematic and d ynamic equations. The novelty in this work is that, an optimal control system se lf-tuning parameters based on an optimization algorithm for these models of the mobile robot is utilized. The optimal control type that is used in this work is the Linear Quadratic Regulator (LQR) controller. LQR is used to control the actu ator torque that is required in each wheel to achieve the robot task. The parame ters of the LQR controller are tuned by using Ant Colony Optimization (ACO). For results simulation, MATLAB/ Simulink is used for circular and infinity shape tr ajectories. Results show that when the robot follows a circular trajectory, the values of position trajectory error values are reduced to smAll value (ex=3.218 *10-5m) and (ey= 2.224*10-5m) in xo and yo directions, respectively and remained almost at these values until the end of the simulation time."
University of TechnologyBaghdadIraqAsiaEmerging TechnologiesMachine LearningRobotRobotics
NETL
NSTL
