基于粒子群优化算法的绳驱动连续体机器人轨迹规划
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1.河北科技大学;2.中国科学院宁波材料技术与工程研究所浙江省机器人与智能制造装备技术重点实验室

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TP

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名称及编号:国家自然科学基金资助项目(51705510);NSFC-浙江两化融合联合基金资助项目(U1909215);中科院创新研究院资助项目(C2018005)


Trajectory planning of a cable-driven continuum robot based on particle swarm optimization algorithm
Author:
Affiliation:

1.Zhejiang Key Laboratory of Robotics and Intelligent Equipment Technology,Ningbo Institute of Materials Technology and Engineering,Chinese Academy of Sciences;2.Hebei University of Science and Technology,Shijiazhuang

Fund Project:

the National Natural Science Foundation of China under Project 51705510;the NSFC-Zhejiang Joint Found for the Integration and Information under Project U1909215 ;the Institute of Robotics and Intelligent Manufacturing Innovation, Chinese Academy of Sciences, under Project C2018005

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    摘要:

    相比于传统刚性机器人,绳驱动连续体机器人环境适应能力强,可以实现狭窄空间的探测和操作,为提高其运动轨迹的平滑性和稳定性,提出了在关节空间和笛卡尔空间分别开展基于样条函数和粒子群算法的轨迹规划研究。首先,采用双参数局部指数积公式建立了连续体机器人的运动学模型,其次,根据牛顿-拉夫森迭代方法求解逆运动学,最后,基于自适应惯性权重的粒子群时间最优化算法结合五次B样条函数,分别实现了连续体机器人在关节空间和笛卡尔空间的轨迹规划。仿真结果表明,在相同的条件下,两种方法均可得到连续体机器人末端的连续轨迹,速度均小于10 mm/s,加速度均小于20 mm/s^2,而基于关节空间规划出的关节位移、速度、加速度曲线更平滑,关节空间规划用时9.219 3 s,笛卡尔空间规划用时10.604 6 s。

    Abstract:

    Different with traditional rigid robots, cable-driven continuum robots are able to working in the narrow space to realize the inspection or detection. To improve the smoothness and stability of its motion trajectory, the trajectory planning method based on spline and particle swarm is proposed for the cable driven continuum robot in its joint space and Cartesian space. Firstly, the kinematic model has been built by using the two parameters local product-of-exponential (POE) formula, Secondly, the inverse kinematic has been solved by using Newton Raphson iterative method. Finally, the particle swarm optimization algorithm based on adaptive inertia weight has been used to solve the time optimal problem and the B-spline function has been used for generate smoothly trajectory, the trajectory planning of the continuum robot in joint space and Cartesian space is realized respectively. The simulation results show that the planned trajectories both in joint space and Cartesian space are continuous. The obtained velocities are less than 10 mm/s and the accelerations are less than 20 mm/s^2. However, the produced position, velocity and acceleration curves are smoother when doing the trajectory planning in joint space. In terms of running time,it takes 9.219 3 s in joint space planning and takes 10.604 6 s in Cartisian space.

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  • 收稿日期:2020-07-16
  • 最后修改日期:2020-07-16
  • 录用日期:2023-09-20
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