采用社会约束自适应动态窗口法的服务机器人路径规划

何丽; 宁子豪; 袁亮; 刘志强

doi:10.7652/xjtuxb202405005

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采用社会约束自适应动态窗口法的服务机器人路径规划

—————————————————————— | 更新时间：2025-07-28

- 采用社会约束自适应动态窗口法的服务机器人路径规划
- Path Planning of Service Robot Based on Social Dynamic Windows Approach Algorithm
- 西安交通大学学报 2024年58卷第5期页码：42-51
- 作者机构：
  
  1. 新疆大学智能制造现代产业学院,乌鲁木齐,830047
  2. 北京化工大学信息科学与技术学院,北京,100029
- 作者简介：
  
  : 2023-10-27。作者简介: 何丽(1986—),女,副教授。基金项目: 国家自然科学基金资助项目(62063033)。
- 基金信息：
  
  : 2023-10-27。作者简介: 何丽(1986—),女,副教授。基金项目: 国家自然科学基金资助项目(62063033)。
- DOI：10.7652/xjtuxb202405005
  中图分类号： TP242.6
- 网络首发：2024-05-10，
  
  纸质出版：2024
- 稿件说明：
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何丽, 宁子豪, 袁亮, 等. 采用社会约束自适应动态窗口法的服务机器人路径规划[J]. 西安交通大学学报, 2024,58(5):42-51.

HE Li, NING Zihao, YUAN Liang, et al. Path Planning of Service Robot Based on Social Dynamic Windows Approach Algorithm[J]. 2024, 58(5): 42-51.
何丽, 宁子豪, 袁亮, 等. 采用社会约束自适应动态窗口法的服务机器人路径规划[J]. 西安交通大学学报, 2024,58(5):42-51. DOI： 10.7652/xjtuxb202405005.

HE Li, NING Zihao, YUAN Liang, et al. Path Planning of Service Robot Based on Social Dynamic Windows Approach Algorithm[J]. 2024, 58(5): 42-51. DOI： 10.7652/xjtuxb202405005.

摘要

针对传统动态窗口法在行人密集环境下动态路径规划存在灵活性差、效率低、安全性缺乏等问题

提出一种社会交互空间下基于社会约束自适应动态窗口法(social_DWA)

并采用其解决服务机器人局部路径规划问题。首先

采用非对称高斯公式对单行人以及多人群组交互空间进行模型化描述; 其次

在传统动态窗口法的基础上

采用动态行人方位角约束对动态行人进行避让; 改进距离评价函数

分类决策与行人、多人群组、一般障碍物的安全距离; 最后

提出速度权重自适应调整策略

优化服务机器人在途经不同密集度社会交互区域时的移动速度。为验证算法有效性

在两种模拟社会场景下

先后开展了social_DWA算法与传统DWA算法、FIDWA算法的路径规划仿真对比实验。结果表明:采用social_DWA算法所消耗的运动时间在场景1中较传统DWA和FIDWA算法分别缩短了1.53、0.43 s

在场景2中较传统DWA和FIDWA算法分别缩短了26.3、2.86 s; 相较于传统DWA算法和FIDWA算法

social_DWA算法能保持有效的行人安全距离

并使运行轨迹更加合理。social_DWA算法在行人避让、环境适应能力等方面具有一定的优越性。

Abstract

To address issues such as poor flexibility

low efficiency

and safety concerns in dynamic path planning in the crowded pedestrian environments

an adaptive dynamic window method based on social constraints(social_DWA)in the social interaction space is proposed

and it is used to solve local path planning problems of service robots. Firstly

the asymmetric Gaussian formula is employed to model interaction spaces of single pedestrian and groups. Secondly

based on the original dynamic window method

the dynamic pedestrian azimuth constraint is implemented to steer clear of dynamic pedestrians. Enhancements are made to the distance evaluation function to classify and ascertain the safety distances from pedestrians

pedestrian groups

and general obstacles. Finally

an adaptive adjustment strategy of speed weight is proposed to optimize the movement speed of service robots while passing through social interaction areas with varying densities. To verify the effectiveness of the algorithm

the path planning simulation experiments of the social_DWA algorithm

the traditional DWA algorithm

and the FIDWA algorithm are carried out in two simulated social scenarios featuring different complexities. The results show that the motion time consumed by the social_DWA algorithm is reduced by 1.53 and 0.43 s compared with the traditional DWA algorithms and FIDWA algorithms in scenario 1

and 26.3 and 2.86 s lower than the traditional DWA algorithms and FIDWA algorithms in scenario 2

respectively.Compared with the traditional DWA algorithm and FIDWA algorithm

the social_DWA algorithm maintains an effective pedestrian safety distance and ensures more rational running trajectories. The validation confirms the social_DWA algorithm's superiority in pedestrian avoidance and environmental adaptability.

关键词

Keywords

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