仅用杆件倾角信息实现大型张拉整体机械臂的高精度形状估计
Proprioceptive Shape Estimation of Tensegrity Manipulators Using Energy Minimisation
- 通过各杆件相对重力的倾角数据，结合能量最小化方法估计整体形状
- 实验显示在1160mm长的五层20杆结构上误差仅占总长2.1%
- 无需外部传感器，适合复杂或远程环境下的自适应控制
形状估计是控制连续弯曲张拉整体机械臂的基础，但至今仍具挑战。尽管外感知传感器实现简单，但成本高且依赖特定环境；而本体感知方法无此限制。现有方法尚未验证适用于大规模张拉整体结构作为机械臂。本文证明，仅需每个杆件相对于重力的倾角信息，即可实现整个机械臂的形状估计。该倾角数据可通过在每根杆上安装惯性测量单元（IMU）轻松获取。在包含20根杆、总长1160mm的五层张拉整体机械臂上进行实验，结果表明：无论初始状态如何，在静态条件下形状估计误差仅为总长度的2.1%，且在外部扰动下仍能保持稳定估计。
原文摘要 · Abstract (English)
Shape estimation is fundamental for controlling continuously bending tensegrity manipulators, yet achieving it remains a challenge. Although using exteroceptive sensors makes the implementation straightforward, it is costly and limited to specific environments. Proprioceptive approaches, by contrast, do not suffer from these limitations. So far, several methods have been proposed; however, to our knowledge, there are no proven examples of large-scale tensegrity structures used as manipulators. This paper demonstrates that shape estimation of the entire tensegrity manipulator can be achieved using only the inclination angle information relative to gravity for each strut. Inclination angle information is intrinsic sensory data that can be obtained simply by attaching an inertial measurement unit (IMU) to each strut. Experiments conducted on a five-layer tensegrity manipulator with 20 struts and a total length of 1160 mm demonstrate that the proposed method can estimate the shape with an accuracy of 2.1 \% of the total manipulator length, from arbitrary initial conditions under both static conditions and maintains stable shape estimation under external disturbances.
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