The inverse kinematics (IK) problem of continuum robots has been investigated in depth in the past decades. Under the constant-curvature bending assumption, closed-form IK solution has been obtained for continuum robots with variable segment lengths. Attempting to close the gap towards a complete solution, this paper presents an efficient solution for the IK problem of 2-segment continuum robots with one or two inextensible segments (a.k.a, constant segment lengths). Via representing the robot's shape as piecewise line segments, the configuration variables are separated from the IK formulation such that solving a one-variable nonlinear equation leads to the solution of the entire IK problem. Furthermore, an in-depth investigation of the boundaries of the dexterous workspace of the end effector caused by the configuration variables limits as well as the angular velocity singularities of the continuum robots was established. This dexterous workspace formulation, which is derived for the first time to the best of the authors' knowledge, is particularly useful to find the closest orientation to a target pose when the target orientation is out of the dexterous workspace. In the comparative simulation studies between the proposed method and the Jacobian-based IK method involving 500,000 cases, the proposed variable separation method solved 100% of the IK problems with much higher computational efficiency.
翻译:在过去几十年中,连续机器人的反动运动(IK)问题得到了深入调查。在常态曲弯曲假设下,已经为具有可变区段长度的连续机器人获得了封闭式 IK 解决方案。为了缩小差距以达成完整的解决方案,本文件为使用一个或两个无法延伸的区段(a.k.a,恒定区段长度)的 IM2 组合连续机器人问题提供了一个有效的解决方案。代表机器人形状成片形的光线段,配置变量与IK 公式分离,这样可以解决一个可变非线性非线性方程式,从而导致整个IK 问题的解决方案。此外,为了深入调查由配置变量限以及连续机器人的角速度奇特性导致的终端效应的宽度工作空间的界限,本文件提出了一种有效的解决方案。 这种光速工作空间配制是首次从作者最了解的角度推导出,因此特别有助于找到最接近目标方向的IK-直线方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方位,在比较方向上的拟议50个对比方法中,在模拟方法中,在提议的可变法方法中选择法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法式法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法法的深度之间方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方方。