Dong Jiaxiang, Liu Quanquan, Li Peng, Wang Chunbao, Zhao Xuezhi, Hu Xiping
School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, China.
Guangdong-Hong Kong-Macao Joint Laboratory, Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen 518172, China.
Biomimetics (Basel). 2025 May 8;10(5):301. doi: 10.3390/biomimetics10050301.
This paper presents a bio-inspired rigid-flexible continuum robot driven by flexible shaft tension-torsion synergy, tackling the trade-off between actuation complexity and flexibility in continuum robots. Inspired by the muscular arrangement of octopus arms, enabling versatile multi-degree-of-freedom (DoF) movements, the robot achieves 6-DoF motion and 1-DoF gripper opening and closing movement with only six flexible shafts, simplifying actuation while boosting dexterity. A comprehensive kinetostatic model, grounded in Cosserat rod theory, is developed; this model explicitly incorporates the coupling between the spinal rods and flexible shafts, the distributed gravitational effects of spacer disks, and friction within the guide tubes. Experimental validation using a physical prototype reveals that accounting for spacer disk gravity diminishes the maximum shape prediction error from 20.56% to 0.60% relative to the robot's total length. Furthermore, shape perception experiments under no-load and 200 g load conditions show average errors of less than 2.01% and 2.61%, respectively. Performance assessments of the distal rigid joint showcased significant dexterity, including a 53° grasping range, 360° continuous rotation, and a pitching range from -40° to +45°. Successful obstacle avoidance and long-distance target reaching experiments further demonstrate the robot's effectiveness, highlighting its potential for applications in medical and industrial fields.
本文提出了一种受生物启发的刚柔连续体机器人,由柔性轴的拉伸 - 扭转协同驱动,解决了连续体机器人在驱动复杂性和灵活性之间的权衡问题。受章鱼臂肌肉排列的启发,能够实现多功能多自由度(DoF)运动,该机器人仅用六根柔性轴就实现了6自由度运动和1自由度夹爪开合运动,在提高灵活性的同时简化了驱动。基于柯塞尔特杆理论建立了一个综合的运动静力学模型;该模型明确纳入了脊柱杆与柔性轴之间的耦合、间隔盘的分布重力效应以及导管内的摩擦力。使用物理原型进行的实验验证表明,考虑间隔盘重力后,相对于机器人的总长度,最大形状预测误差从20.56%降至0.60%。此外,在空载和200 g负载条件下的形状感知实验显示平均误差分别小于2.01%和2.61%。远端刚性关节的性能评估展示了显著的灵活性,包括53°的抓取范围、360°的连续旋转以及 - 40°至 + 45°的俯仰范围。成功的避障和远距离目标到达实验进一步证明了该机器人的有效性,突出了其在医疗和工业领域的应用潜力。