首页|New Robotics Data Have Been Reported by Researchers at State University of New Y ork (SUNY) Buffalo (A Variable Stiffness Endof-arm Tooling Mechanism To Enhance Dynamic Task Capabilities of Robotic Manipulators)
New Robotics Data Have Been Reported by Researchers at State University of New Y ork (SUNY) Buffalo (A Variable Stiffness Endof-arm Tooling Mechanism To Enhance Dynamic Task Capabilities of Robotic Manipulators)
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-Current study results on Robotics have been published. According to news reporting originating in Buffalo, New York, b y NewsRx journalists, research stated, "Variable stiffness end-of-arm actuators can add dynamic manipulation capabilities to stiff manipulators and simultaneous ly enhance safety. The presence of an elastic element in these actuators can be used for absorbing impact energy; or storing energy and utilizing it for perform ing explosive tasks." The news reporters obtained a quote from the research from the State University of New York (SUNY) Buffalo, "The major challenge with variable stiffness actuato rs is to control their position and stiffness simultaneously to achieve optimal task performance. In this paper, we present an end-of-arm variable stiffness mec hanism (VSM) for performing dynamic tasks. We formulate the task as an optimal c ontrol problem and numerically solve for the task-specific stiffness profile. We demonstrate the usability of the optimization problem in exploiting the dynamic s of the VSM during an explosive hammering task and demonstrate that the time-va rying stiffness profile can store energy and leads to improved task performance. As a result, the hammer attains twice as much velocity with variable stiffness compared to fixed stiffness. The hammering performance is further improved by op timizing task completion time and hammer velocity. Moreover, we demonstrate that the VSM stiffness plays a crucial role in minimizing the impact forces transfer red to the robot."
BuffaloNew YorkUnited StatesNorth and Central AmericaEmerging TechnologiesMachine LearningRoboticsRobotsState University of New York (SUNY) Buffalo
NETL
NSTL
