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Article
Publication date: 16 July 2024

Peng Wu, Heng Su, Hao Dong, Tengfei Liu, Min Li and Zhihao Chen

Robotic arms play a crucial role in various industrial operations, such as sorting, assembly, handling and spraying. However, traditional robotic arm control algorithms often…

Abstract

Purpose

Robotic arms play a crucial role in various industrial operations, such as sorting, assembly, handling and spraying. However, traditional robotic arm control algorithms often struggle to adapt when faced with the challenge of dynamic obstacles. This paper aims to propose a dynamic obstacle avoidance method based on reinforcement learning to address real-time processing of dynamic obstacles.

Design/methodology/approach

This paper introduces an innovative method that introduces a feature extraction network that integrates gating mechanisms on the basis of traditional reinforcement learning algorithms. Additionally, an adaptive dynamic reward mechanism is designed to optimize the obstacle avoidance strategy.

Findings

Validation through the CoppeliaSim simulation environment and on-site testing has demonstrated the method's capability to effectively evade randomly moving obstacles, with a significant improvement in the convergence speed compared to traditional algorithms.

Originality/value

The proposed dynamic obstacle avoidance method based on Reinforcement Learning not only accomplishes the task of dynamic obstacle avoidance efficiently but also offers a distinct advantage in terms of convergence speed. This approach provides a novel solution to the obstacle avoidance methods for robotic arms.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 2 January 2024

Wenyue Tang, Tengfei Zhang and Yang Yang

This study aims to discuss the formation mechanism of members’ emotional attachment to virtual travel communities from an online–offline perspective, focusing on the role of…

Abstract

Purpose

This study aims to discuss the formation mechanism of members’ emotional attachment to virtual travel communities from an online–offline perspective, focusing on the role of offline tourism experiences.

Design/methodology/approach

A questionnaire was designed to survey active travel enthusiast clubs that hold frequent offline tourism activities. A structural equation modeling method was used to estimate the model and test the research hypotheses.

Findings

Results demonstrated that offline travel experiences positively influenced online community attachment (i.e., community dependence and identity), and this effect was more pronounced than that of one’s sense of community (i.e., belonging, trust and immersion) on community attachment. Therefore, compared with online interaction, offline travel experiences played a greater part in strengthening virtual community attachment.

Originality/value

The study presents a pioneering effort on understanding how offline activities help shape the community attachment to virtual communities.

研究目的

本研究从线上-线下的角度探讨了人们对虚拟旅行社区的情感依恋形成机制, 着重关注线下旅游体验的作用。

研究方法

本研究设计了问卷, 对经常举办线下旅游活动的驴友俱乐部进行了调查。采用结构方程建模方法估计模型并验证研究假设。

研究发现

结果表明, 线下旅游体验积极地影响着线上社区依恋, 并且这种影响比社区感对社区依恋的影响更为显著。因此, 相较于线上互动, 线下旅游体验在增强虚拟社区依恋方面起到了更大的作用。

研究创新

本研究首次探讨了线下活动如何帮助塑造虚拟社区成员对虚拟社区的依恋。

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