首页|Study Results from School of Mechanical Engineering Broaden Understanding of Robotics (Bi-Objective Function Optimization for Welding Robot Parameters to Improve Manipulability)
Study Results from School of Mechanical Engineering Broaden Understanding of Robotics (Bi-Objective Function Optimization for Welding Robot Parameters to Improve Manipulability)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Research findings on robotics are disc ussed in a new report. According to newsoriginating from Busan, South Korea, by NewsRx correspondents, research stated, “This paper presentsa study on optimal design to determine the installation position and link lengths of a robot withi n adesignated workspace for welding, aiming to minimize singularities during th e robot’s motion.”The news correspondents obtained a quote from the research from School of Mechan ical Engineering:“Bi-objective functions are formulated to minimize singulariti es while maximizing the volumes of linearvelocity manipulability ellipsoid and angular velocity manipulability ellipsoid, respectively, ensuring isotropy.We h ave constructed a simulation environment incorporating PID control to account fo r robot trackingerrors. This environment was utilized as a simulator to derive a Bi-objective function set within a geneticalgorithm. Through this, we optimiz ed four robot link length variables and two installation positionvariables, sel ecting the optimal design variables on the Pareto Front.”
School of Mechanical EngineeringBusanSouth KoreaAsiaEmerging TechnologiesMachine LearningRobotRobotics
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