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THE DIMENSIONAL SYNTHESIS OF THE LINEAR DELTA ROBOT FOR A FORCE-FEEDBACK DEVICE

机译:力反馈装置的线性Delta机器人的三维综合

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We perform the dimensional synthesis of a parallel manipulator to be used as a force-feedback device in a virtual reality application for surgeon training in prostate brachytherapy. For such brachytherapy operations, the characteristics of the required workspace point towards the architecture of the linear DELTA robot to be used as the force-feedback device to the surgeon. In this paper, we address the dimensional synthesis of the linear DELTA robot for the prescribed workspace. To this end, we propose the minimum relative kinematic sensitivity as an objective function, a kinematic performance index that is different from most of the commonly used metrics, i.e., manipulability and dexterity. The minimum relative kinematic sensitivity represents the ratio of the minimum to the maximum effect of a unity-bounded set of actuator displacements on the moving-platform pose. These extremum sensitivities are computed independently over the prescribed workspace. Thence, the dimensional synthesis problem consists in finding the robot dimensions that maximize the minimum relative kinematic sensitivity, so it is guaranteed within a narrow interval over the prescribed workspace. This optimization problem is nonconvex, which poses a challenge from the computational point of view. However, because of symmetry in the mechanism and other simplifications, the number of optimization variables is reduced to four. This allows a reasonably fine discretization of the search domain, giving the designers confidence that the ensuing local optimum is close to the global optimum.
机译:我们执行并行操纵器的尺寸合成,以在前列腺癌近距离放射治疗的虚拟现实应用中用作力反馈设备。对于此类近距离放射疗法操作,所需工作空间的特征指向线性DELTA机器人的体系结构,该机器人将用作外科医生的力反馈设备。在本文中,我们针对指定工作空间解决了线性DELTA机器人的尺寸合成问题。为此,我们提出了最小相对运动灵敏度作为目标函数,该运动性能指标不同于大多数常用度量,即可操纵性和灵巧性。最小相对运动灵敏度表示在移动平台姿态上一组统一边界的致动器位移的最小作用与最大作用之比。这些极值灵敏度是在规定的工作空间内独立计算的。因此,尺寸综合问题在于找到使最小相对运动灵敏度最大化的机器人尺寸,因此可以保证在规定的工作空间内的狭窄间隔内。这个优化问题是非凸的,这从计算的角度提出了挑战。但是,由于机制的对称性和其他简化原因,优化变量的数量减少到四个。这允许对搜索域进行合理的离散化,从而使设计人员有信心确保随后的局部最优接近全局最优。

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