Keyvanara Mahboubeh, Goshtasbi Arman, Kuling Irene A
Reshape Lab, Dynamics and Control Group, Department of Mechanical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands.
SDU Soft Robotics, SDU Biorobotics, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark (SDU), 5230 Odense, Denmark.
Sensors (Basel). 2023 Aug 3;23(15):6882. doi: 10.3390/s23156882.
Soft robots are interesting examples of hyper-redundancy in robotics. However, the nonlinear continuous dynamics of these robots and the use of hyper-elastic and visco-elastic materials make modeling these robots more complicated. This study presents a geometric inverse kinematics (IK) model for trajectory tracking of multi-segment extensible soft robots, where each segment of the soft actuator is geometrically approximated with a rigid links model to reduce the complexity. In this model, the links are connected with rotary and prismatic joints, which enable both the extension and rotation of the robot. Using optimization methods, the desired configuration variables of the soft actuator for the desired end-effector positions were obtained. Furthermore, the redundancy of the robot is applied for second task applications, such as tip angle control. The model's performance was investigated through kinematics and dynamics simulations and numerical benchmarks on multi-segment soft robots. The results showed lower computational costs and higher accuracy compared to most existing models. The method is easy to apply to multi-segment soft robots in both 2D and 3D, and it was experimentally validated on 3D-printed soft robotic manipulators. The results demonstrated the high accuracy in path following using this technique.
软体机器人是机器人技术中超冗余的有趣实例。然而，这些机器人的非线性连续动力学以及超弹性和粘弹性材料的使用使得对这些机器人进行建模变得更加复杂。本研究提出了一种用于多段可伸展软体机器人轨迹跟踪的几何逆运动学（IK）模型，其中软驱动器的每一段都用刚性连杆模型进行几何近似，以降低复杂性。在该模型中，连杆通过旋转关节和棱柱关节连接，这使得机器人既能伸展又能旋转。使用优化方法，获得了软驱动器针对期望末端执行器位置的期望配置变量。此外，机器人的冗余性被应用于第二任务应用，如尖端角度控制。通过对多段软体机器人的运动学和动力学模拟以及数值基准测试，研究了该模型的性能。结果表明，与大多数现有模型相比，该模型具有更低的计算成本和更高的精度。该方法易于应用于二维和三维的多段软体机器人，并且在3D打印的软体机器人操纵器上进行了实验验证。结果证明了使用该技术在路径跟踪方面的高精度。
