基于姿态解算的外肢体手指抓取增强量化分析和优化设计

Quantitative Analysis and Optimal Design of Grasp Augmentation of Supernumerary Robotic Finger Based on Pose Solving

  • 摘要: 外肢体手指是一种通过为人体增加额外的肢体实现运动增强的可穿戴机器人,但目前抓取增强效果有限。针对此问题,研究了基于外肢体手指和人手位姿的最大可抓取球体解算方法,通过对外肢体手指的量化分析,对其进行优化设计,从而增强抓取能力。首先,构建了人手和外肢体手指的D-H(Denavit-Hartenberg)运动学模型,使用蒙特卡洛法得到人手和外肢体手指位姿库,并基于该库提出一种半包络稳定抓取球体的解析方法。然后,基于外肢体手指与人手能够抓取的球体的最大半径定义并量化了外肢体手指的抓取增强能力,并基于该能力对外肢体在3个穿戴位置处的杆长尺寸进行优化。最后,根据受试者手部尺寸及3个穿戴位置处在优化前后的杆长系数,搭建了外肢体手指样机,并对半径2~12 cm的球体进行了抓取实验。实验结果表明,杆长系数优化后,3个穿戴位置处的抓取能力分别增强了42.4%、38.5%和7.91%,证明了解算方法的正确性和有效性

     

    Abstract: Supernumerary robotic finger (SRF) is a wearable robot that achieves motion enhancement by augmenting additional limbs for the human body, however the grasp augmentation effect is limited. To address this problem, a maximum graspable sphere solution method based on SRF and hand pose is investigated to enhance the grasping ability, and the SRF design is optimized by quantitative analysis. Firstly, the D-H (Denavit-Hartenberg) kinematic models of the human hand and SRF are constructed, the finger pose library of the human hand and SRF is obtained by the Monte Carlo method, and an analytical method to achieve stable semi-envelope grasping of the sphere is proposed based on this library. Then, the grasp augmentation ability of SRF is defined and quantified based on the radius of the maximum graspable sphere of SRF and human hand, and the rod lengths of SRF at 3 wearing positions are optimized based on this ability. Finally, the SRF prototypes are built based on the subject's hand size and the rod lengths at 3 wearing positions before and after optimization, with which the grasping experiments are carried out on spheres with radius of 2~12 cm. The experimental results show that the grasping abilities at the 3 wearing positions are enhanced by 42.4%, 38.5% and 7.91% respectively after rod length optimization, which proves the correctness and effectiveness of the solution method.

     

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