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Article
Publication date: 1 February 2021

Shuhuan Wen, Xiaohan Lv, Hak Keung Lam, Shaokang Fan, Xiao Yuan and Ming Chen

This paper aims to use the Monodepth method to improve the prediction speed of identifying the obstacles and proposes a Probability Dueling DQN algorithm to optimize the…

Abstract

Purpose

This paper aims to use the Monodepth method to improve the prediction speed of identifying the obstacles and proposes a Probability Dueling DQN algorithm to optimize the path of the agent, which can reach the destination more quickly than the Dueling DQN algorithm. Then the path planning algorithm based on Probability Dueling DQN is combined with FastSLAM to accomplish the autonomous navigation and map the environment.

Design/methodology/approach

This paper proposes an active simultaneous localization and mapping (SLAM) framework for autonomous navigation under an indoor environment with static and dynamic obstacles. It integrates a path planning algorithm with visual SLAM to decrease navigation uncertainty and build an environment map.

Findings

The result shows that the proposed method offers good performance over existing Dueling DQN for navigation uncertainty under the indoor environment with different numbers and shapes of the static and dynamic obstacles in the real world field.

Originality/value

This paper proposes a novel active SLAM framework composed of Probability Dueling DQN that is the improved path planning algorithm based on Dueling DQN and FastSLAM. This framework is used with the Monodepth depth image prediction method with faster prediction speed to realize autonomous navigation in the indoor environment with different numbers and shapes of the static and dynamic obstacles.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 18 October 2019

Shuhuan Wen, Xueheng Hu, Zhen Li, Hak Keung Lam, Fuchun Sun and Bin Fang

This paper aims to propose a novel active SLAM framework to realize avoid obstacles and finish the autonomous navigation in indoor environment.

264

Abstract

Purpose

This paper aims to propose a novel active SLAM framework to realize avoid obstacles and finish the autonomous navigation in indoor environment.

Design/methodology/approach

The improved fuzzy optimized Q-Learning (FOQL) algorithm is used to solve the avoidance obstacles problem of the robot in the environment. To reduce the motion deviation of the robot, fractional controller is designed. The localization of the robot is based on FastSLAM algorithm.

Findings

Simulation results of avoiding obstacles using traditional Q-learning algorithm, optimized Q-learning algorithm and FOQL algorithm are compared. The simulation results show that the improved FOQL algorithm has a faster learning speed than other two algorithms. To verify the simulation result, the FOQL algorithm is implemented on a NAO robot and the experimental results demonstrate that the improved fuzzy optimized Q-Learning obstacle avoidance algorithm is feasible and effective.

Originality/value

The improved fuzzy optimized Q-Learning (FOQL) algorithm is used to solve the avoidance obstacles problem of the robot in the environment. To reduce the motion deviation of the robot, fractional controller is designed. To verify the simulation result, the FOQL algorithm is implemented on a NAO robot and the experimental results demonstrate that the improved fuzzy optimized Q-Learning obstacle avoidance algorithm is feasible and effective.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 13 February 2019

Chi Keung Charles Fung and Chi Shun Fong

Many scholars would agree that the international status of Hong Kong is one of the crucial factors that contribute to the continued success of Hong Kong. However, few of…

Abstract

Purpose

Many scholars would agree that the international status of Hong Kong is one of the crucial factors that contribute to the continued success of Hong Kong. However, few of them explain the origin of Hong Kong’s international status. The purpose of this paper is to fill this literature gap through the case study of Hong Kong’s admission to an international organization – the Asian Development Bank (ADB) – in the late 1960s.

Design/methodology/approach

Based on declassified archives, a historical approach has been adopted to trace the origin of Hong Kong’s international status.

Findings

The findings suggest that Cold War geopolitics, both local and regional level, explain why Hong Kong, even though remained as a dependent territory of Britain, became a member of an international organization independent from the British influence. While geopolitics at local level incentivized the colonial government to “go out” for external support, geopolitics at the regional level provided an opportunity for Hong Kong to acquire membership of the ADB.

Originality/value

This paper is among the first academic study on the origin of Hong Kong’s international status.

Details

Asian Education and Development Studies, vol. 8 no. 2
Type: Research Article
ISSN: 2046-3162

Keywords

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