Structure optimization and analysis of pole-climbing robot based on SIMP method

doi:10.3785/j.issn.1006-754X.2023.00.042

Chin J Eng Design

2023, Vol. 30

Issue (3): 342-352 DOI: 10.3785/j.issn.1006-754X.2023.00.042

Robotic and Mechanism Design

Structure optimization and analysis of pole-climbing robot based on SIMP method

Xiaofei ZHENG(

),Zhenhai HUANG,Xiaolong MA,Jianxin WANG,Binrui WANG(

)

College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China

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Abstract

In order to achieve the structural compactness and lightweight design of pole-climbing robots, and overcome the difficulty of vertical pole movement, the weight reduction can be realized by reducing the thickness of parts. However, it can cause local stress concentration, resulting in insufficient stiffness of robot structure. Therefore, starting from the morphology of inchworms, the SIMP (solid isotropic material with penalization) variable density topology optimization design was carried out for the main structure of the pole-climbing robot, realizing the lightweight design of the robot while ensuring its overall performance. Firstly, the main components such as the gripper and T-joint of the pole-climbing robot were selected as the objects, and three motion gaits were dynamically simulated by ADAMS simulation software to simulate the load changes caused by the three motion gaits under extreme working conditions. Then, the boundary conditions were set based on information such as extreme working condition loads. The Topology Optimization module in ANSYS Workbench software was used to perform SIMP variable density topology optimization on the pole-climbing robot to remove the redundant materials that were slightly affected by loads from the robot structure. The optimized robot model was reconstructed and compared with before optimization. The results showed that while the overall weight of the pole-climbing robot was reduced by 7.6% (from 13.60 kg to 12.57 kg), the comprehensive performance of the gripper and T-joint with larger force was improved. The experimental results of energy consumption test showed that the operating energy consumption of the optimized pole-climbing robot decreased by 7.0% compared with before optimization. The proposed SIMP variable density topology optimization method has a high reference value in the structural design of biomimetic pole-climbing robots.

Key words： robot motion gait structural analysis topology optimization variable density

Received: 10 January 2023 Published: 06 July 2023

CLC:

TH 164

Corresponding Authors: Binrui WANG E-mail: zhengxiaofei.xyz@126.com;wangbrpaper@163.com

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Cite this article:

Xiaofei ZHENG,Zhenhai HUANG,Xiaolong MA,Jianxin WANG,Binrui WANG. Structure optimization and analysis of pole-climbing robot based on SIMP method. Chin J Eng Design, 2023, 30(3): 342-352.

URL:

https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2023.00.042 OR https://www.zjujournals.com/gcsjxb/Y2023/V30/I3/342

基于SIMP方法的爬杆机器人结构优化与分析

为了实现爬杆机器人的结构紧凑和轻量化设计，以及克服垂直爬杆运动困难的问题，可通过减小零件厚度的方法来进行减重，但这会造成局部应力集中，导致机器人结构刚度不足。为此，从尺蠖的形态出发，对爬杆机器人的主要结构进行SIMP（solid isotropic material with penalization，具有惩罚作用的固体各向同性材料）变密度拓扑优化设计，在保证机器人整体性能的基础上实现轻量化设计。首先，选取爬杆机器人的夹持器与T关节等主要部件为对象，通过ADAMS仿真软件对3种运动步态进行动态仿真，模拟了在极限工况下3种运动步态引起的载荷变化。然后，根据极限工况载荷等信息设置边界条件，通过ANSYS Workbench软件中的Topology Optimization模块对爬杆机器人进行SIMP变密度拓扑优化，去除机器人结构中受载荷影响微小的冗余材料，对优化后的机器人模型进行重构并与优化前对比。结果表明，在爬杆机器人整机质量减小了7.6%（由13.60 kg减小为12.57 kg）的同时，受力较大的夹持器和T关节的综合性能有所提高。能耗测试实验结果表明，优化后爬杆机器人的运行能耗比优化前降低了7.0%。所提出的SIMP变密度拓扑优化方法在仿生爬杆机器人的结构设计中具有较高的参考价值。

关键词： 机器人, 运动步态, 结构分析, 拓扑优化, 变密度

Fig.1 Self-made 5-DOF series pole-climbing robot

Fig.2 Topology optimization process of pole-climbing robot based on SIMP variable density method

Fig.3 Three motion gaits of pole-climbing robot

Fig.4 Load and torque change curves of gripper

Fig.5 Load and torque change curves of T-joint under different motion gaits

Fig.6 Cloud maps of equivalent stress and equivalent deformation of gripper

Fig.7 Cloud maps of equivalent stress and equivalent deformation of T-joint swinging component

Fig.8 Cloud maps of equivalent stress and equivalent deformation of T-joint connection seat

Fig.9 Topology optimization cloud map of gripper

Fig.10 Optimized gripper model

Fig.11 Topology optimization cloud map of T-joint swinging component

Fig.12 Topology optimization cloud map of T-joint connection seat

Fig.13 Optimized T-joint swinging component model

Fig.14 Optimized T-joint connection seat model

Fig.15 Cloud maps of equivalent stress and equivalent deformation of optimized gripper

Table 1 Comparison of quality and mechanical properties of gripper before and after optimization

Fig.16 Cloud maps of equivalent stress and equivalent deformation of optimized T-joint swinging component

Table 2 Comparison of quality and mechanical properties of T-joint swinging component before and after optimization

Fig.17 Cloud maps of equivalent stress and equivalent deformation of optimized T-joint connection seat

Table 3 Comparison of quality and mechanical properties of T-joint connection seat before and after optimization

Fig.18 Energy consumption simulation model of optimized pole-climbing robot

Fig.19 Simulation results of energy consumption of pole- climbing robot before and after optimization

Fig.20 Energy consumption experiment on peristaltic gait of pole-climbing robot prototype

Fig.21 Comparison of simulation results and experimental results of energy consumption of pole-climbing robot


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