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Article
Automation & Control Systems
Zenan Lin et al.
Summary: This paper presents a two-layer path-planning method that utilizes an optimized artificial potential field method and an improved dynamic window approach at the global and local layer, respectively. By incorporating a new repulsive field and utilizing particle swarm optimization for obstacle influence range, the robot is able to plan a better path under multi-obstacle environments. Additionally, a fuzzy control scheme based on collision risk index and relative distance is adopted for evaluating the danger level of moving obstacles at the local path planning level. This method allows the robot to plan a shorter and smoother path while quickly reacting to and avoiding moving obstacles.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2022)
Article
Engineering, Industrial
Van-Thai Nguyen et al.
Summary: In this paper, an artificial intelligence-based maintenance approach is proposed, which uses artificial neural network for predicting maintenance cost at system level and employs deep reinforcement learning algorithm for optimizing maintenance decisions. The experimental results demonstrate the effectiveness of this approach in maintenance cost forecasting and decision optimization.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Automation & Control Systems
Xinbo Yu et al.
Summary: An adaptive impedance controller for human-robot co-transportation is proposed in this research. It utilizes vision and force sensing to obtain human hand position in task space, ensuring safe interaction and smooth control behavior during the transportation task.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Biology
Ilayda Yag et al.
Summary: This study develops a new hybrid classification model using machine learning and deep learning algorithms, supported by swarm optimization-based feature selection, for real-time classification of diseases in apple, grape, and tomato plants. Experimental results show that the model achieves high accuracy in real-time classification of plant leaf diseases.
Article
Computer Science, Information Systems
Tianrui Zhang et al.
Summary: This article studies hybrid path planning models, such as multi-robot path planning and formation cooperative control, to solve the problem of insufficient task execution capability of a single robot under complex conditions. By improving the particle swarm algorithm and the artificial potential field method, global and local path planning models are proposed to enhance the path exploration capability and handling efficiency of robot formation.
Article
Chemistry, Analytical
Christyan Cruz Ulloa et al.
Summary: Recent technological breakthroughs have revolutionized fields such as machine vision and search and rescue robotics, with the application of new and improved neural networks combined with modern optical sensors like thermal cameras for victim identification in post-disaster environments. Robotic teams equipped with specific sensors have been developed for primary intervention tasks in high-risk post-disaster environments. Through testing and validation, a novel automatic method utilizing thermal image processing and CNN has shown over 90% efficiency in victim identification.
Article
Chemistry, Analytical
S. M. Yang et al.
Summary: A safe path planning algorithm for obstacle avoidance in autonomous vehicles has been developed, which integrates path pruning, smoothing, and optimization to improve planning efficiency. This improved algorithm has been shown to successfully track paths and reduce deviations in both regular driving and lane changes.
Article
Automation & Control Systems
Xinbo Yu et al.
Summary: This article proposes a hybrid framework using visual and force sensing for human-robot co-carrying tasks, achieving motion synchronization and stable interaction behavior between human and robot. The framework's effectiveness is validated through simulations and experiments.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Computer Science, Artificial Intelligence
Yi Gan et al.
Summary: The newly proposed 1-0 Bg-RRT algorithm can solve path planning problems in complex environments more quickly and effectively, with better performance compared to traditional RRT and Bg-RRT algorithms.
NEURAL PROCESSING LETTERS
(2021)
Article
Engineering, Marine
Junmin Mou et al.
Summary: In a Man Overboard incident, a quick and effective Search and Rescue operation is crucial for survival. Determining the search area and planning paths for rescue ships are essential, with the main aims of quick arrival and high probability of success. A cooperative path planning framework using Maritime Autonomous Surface Ships is proposed for maximizing success in a time-sensitive operation.
Article
Robotics
Jing Zhang et al.
Summary: This article presents a novel path planning algorithm for autonomous land vehicles, which improves upon the shortcomings of the traditional A-Star algorithm by combining the artificial potential field method. The proposed algorithm enhances efficiency in path planning and makes the path smoother for easier control of autonomous land vehicles.
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
(2021)
Article
Computer Science, Information Systems
Yanli Chen et al.
Summary: This study proposes an improved ACO-APF algorithm for path planning of USVs, which combines ant colony optimization and artificial potential field algorithms to enhance efficiency and safety in dynamic environments.
Article
Computer Science, Information Systems
Qi Song et al.
Article
Computer Science, Artificial Intelligence
Milad Nazarahari et al.
EXPERT SYSTEMS WITH APPLICATIONS
(2019)
Article
Energy & Fuels
P. Kofinas et al.
Article
Computer Science, Artificial Intelligence
Yijing Zhao et al.
KNOWLEDGE-BASED SYSTEMS
(2018)
Article
Multidisciplinary Sciences
Han-ye Zhang et al.
Article
Automation & Control Systems
Huili Yu et al.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2015)
Article
Multidisciplinary Sciences
Volodymyr Mnih et al.