一种IPRRT的机械臂三维路径避障算法

钟华庚; 丁健; 郭永欢; 罗高生; 王芳; 冯玮

doi:10.13433/j.cnki.1003-8728.20220176

一种IPRRT的机械臂三维路径避障算法

doi: 10.13433/j.cnki.1003-8728.20220176

钟华庚^{1, 2,},
丁健²,
郭永欢²,
罗高生^{1, 2, ,},
王芳^{1, 2},
冯玮³

1.
上海海洋大学工程学院上海海洋可再生能源工程技术研究中心，上海　201306
2.
上海海洋大学海洋科学学院上海深渊科学工程技术研究中心，上海　201306
3.
中集海洋工程有限公司，广东深圳，518052

基金项目: 国家自然科学基金面上项目（52071203）、上海市科技攻关计划项目（20dz1206500）、上海市科委自然科学基金面上项目（19ZR1422700）及上海市工程技术研究中心建设计划（19DZ2254800）

详细信息

作者简介:
钟华庚（1996−），硕士研究生，研究方向为路径规划，基于ROS系统的水下机器人控制研究，1142790610@qq.com

通讯作者:
罗高生，讲师，gsluo@shou.edu.cn

中图分类号: TP241.3
计量
- 文章访问数: 116
- HTML全文浏览量: 50
- PDF下载量: 22
- 被引次数: 0
出版历程
- 收稿日期: 2021-11-10
- 刊出日期: 2023-12-25

An Improved Rapidly-exploring Random Tree Algorithm for Manipulator's 3D Path Obstacle Avoidance

ZHONG Huageng^{1, 2
,},
DING Jian²,
GUO Yonghuan²,
LUO Gaosheng^{1, 2
, ,},
WANG Fang^{1, 2},
FENG Wei³

1.
Shanghai Engineering Research Center of Marine Renewable Energy, College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China
2.
Shanghai Engineering Research Center of Hadal Science and Technology, College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
3.
CIMC Offshore Engineering Co., Ltd., Shenzhen 518052, Guangdong, China

摘要

摘要: 标准RRT（Rapidly exploring random tree）算法进行路径规划时，存在规划时间长、规划路径质量差的问题。针对以上问题，提出一种IPRRT算法（Improved RRT algorithm），首先通过重选父节点环节策略剔除冗余路段，区域排斥机制剔除冗余节点，缩短规划路径与规划时间；其次采用线段转角限位与评估函数提升路径质量，最后采用三次Hermite曲线对路径进行平滑处理；通过对深海机械臂进行仿真实验，验证了IPRRT算法的有效性。
- RRT /
- 机械臂 /
- 路径规划 /
- 三次Hermite曲线 /
- ROS系统
Abstract: The standard rapidly-exploring random tree algorithm for path planning takes a long time and has poor path quality. Therefore, an improved rapidly-exploring random tree algorithm is proposed. Firstly, redundant sections are eliminated by using the re-selecting parent node link strategy, and redundant nodes are eliminated with the regional exclusion mechanism to shorten the planning path and time. Secondly, the line segment angle limit and the evaluation function are used to improve the path quality. Finally, the cubic Hermite curve is used to smooth the path. The simulation of a deep-sea manipulator verifies the effectiveness of the improved rapidly-exploring random tree algorithm.
- RRT /
- mechanical arm /
- path planning /
- cubic Hermite curve /
- robot operating system

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图 1 深海四自由度机械臂

Figure 1. Deep-sea four-degrees-of-freedom robotic arm

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图 2 深海四自由度机械手简化结构及其D-H坐标系

Figure 2. Simplified structure of the deep-sea four-degrees-of-freedom robotic hand and its D-H coordinate system

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图 3 机械臂关节与连杆简化过程

Figure 3. Simplification process of the robotic arm's joints and links

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图 4 简化机械臂与外部障碍物碰撞情况

Figure 4. Collision between simplified robotic arm and external obstacles

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图 5 X_new重选父节点的过程

Figure 5. The process of re-selecting parent nodes for X_new

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图 6 区域排斥机制

Figure 6. Regional exclusion mechanism

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图 7 线段转角限位策略

Figure 7. Line segment corner limitation strategy

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图 8 平滑度计算的路径段

Figure 8. Path segment for smoothness calculation

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图 9 三次Hermite曲线平滑处理

Figure 9. Smoothing process using the cubic Hermite curve

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图 10 5种算法性能展示以及后处理效果（二维）

Figure 10. Performance display of five algorithms and post-processing effects (2D)

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图 11 5种算法性能展示以及后处理效果（三维）

Figure 11. Performance display of five algorithms and post-processing effects (3D)

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图 12 ARM 5EMINI机械臂水下工作

Figure 12. ARM 5EMINI robotic arm working underwater

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图 13 无人潜水器（马里亚纳海沟）海试

Figure 13. Unmanned submersible sea trial in the Mariana trench

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图 14 改进算法避障性能测试

Figure 14. Obstacle avoidance performance test of the improved algorithm

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表 1 深海机械手连杆参数表

Table 1. Deep-sea robotic hand link parameters

$ i $	$ {\alpha _{i - 1}} $	$ {a_{i - 1}} $	$ d_i $	$ \theta_{i} $
1	0	0	0	$ {\mathop q\limits^ * }_1 $
2	−90°	$a_{1}=0.061 \mathrm{ ~ m}$	0	$ {\mathop q\limits^ * }_2 $
3	0	$ a_{2}=0.315 \mathrm{ ~ m} $	0	$ {\mathop q\limits^ * }_3 $
4	90°	0	0	$ {\mathop q\limits^ * }_4 $
5	0	0	${d_4} = 0.257 \mathrm{ ~ m}$	0

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Regional exclusion strategy
1：X_rand ← RANDOM_FUCTION（）；
2：if　OBSTACLE_COLLISION（X_near，X_new）
3：X_near ←NEAREST_TREE （T，X_rand）：
4：if　$ {({X_1} - {X_2})^2} + {({Y_1} - {Y_2})^2} > {\psi ^2} $
5： return X_rand
6： else
7： return Null
8： end if
9： else
10： return Null
11：end if

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表 2 5种算法100次仿真实验数据（二维）

Table 2. Data from 100 simulations for five algorithms (2D)

算法类型	规划时间/s	节点总数/个	路径节点数/个	路径规划长度/cm	$\alpha_{\rm{ Max}} > {60^ \circ }$/次
算法1（标准RRT）	10.71	184.80	23.02	450.54	100
算法2	2.54	54.21	20.95	409.16	95
算法3	2.05	45.23	21.09	414.58	97
IPRRT算法	0.95	21.28	5.89	357.58	0
RRT*算法	14.43	434.84	17.94	364.10	34
注：$\alpha_{\rm{ max}} > {60^ \circ }$/次表示为100次路径规划中，单次路径线段转角最大值大于60°的次数。

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表 3 5种算法100次仿真实验数据（三维）

Table 3. Data from 100 simulations for five algorithms (3D)

算法类型	规划时间/s	节点总数/个	路径节点数/个	路径规划长度/cm	$\alpha_{\rm{max}} > {60^ \circ }$/次
算法1（标准RRT）	81.16	1352.90	32	628.38	100
算法2	4.32	70.29	26.25	515.23	99
算法3	3.79	57.06	26.04	510.40	100
IPRRT算法	1.62	21.56	4.94	440.62	0
RRT*算法	412.21	4092.62	21.32	457.64	52

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表 4 不同算法路径平滑度

Table 4. Path smoothness of different algorithms

标准RRT算法	RRT*算法	IPRRT算法
326.21	97.85	23.94

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表 5 深海机械臂规划数据

Table 5. Planning data for deep-sea robotic arm

算法类型	规划平均时间/s	规划成功次数	成功率/%
标准RRT（地图1）	0.351	18	90
IPRRT	0.017	20	100
标准RRT（地图2）	0.288	19	95
IPRRT	0.0139	20	100

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