检索结果-内蒙古大学图书馆

Mobile robot path planning using multi-objective genetic algorithm in industrial automation

SOFT COMPUTING 2022年第15期26卷 7387-7400页

作者： Suresh, K. S. Venkatesan, R. Venugopal, S. SASTRA Deemed Univ Sch Comp Thanjavur Tamil Nadu India Natl Inst Technol Dimapur Nagaland India

Mobile robot path planning problem is a significant research area in industrial automation, which is to determine an optimal path for a robot to reach the destination by avoiding obstacles. Path planning (PP) is one of the most researched topics in mobile robotics. Deriving an optimal path from a huge number of feasible paths for a given environment is called a PP problem. The existing optimization techniques are used to consider path safety, path length, and path smoothness. The conventional optimization techniques implemented for the mobile robot path planning problem incur a lot of cost due to the high complexity to solve. In order to find the optimal path for handling the mobile robot path planning problem, the mobile robot path search based on multi-objective genetic algorithm (MRPS-MOGA) is proposed. The MRPS-MOGA is designed with the novelty of genetic algorithm with multiple objective function to solve mobile robot path planning problems. Hence the proposed MRPS-MOGA handles five different objectives such as safety, distance, smoothness, traveling time, and collision-free path to obtain optimal path. The MOGA is applied to select an optimal path among multiple as well as feasible paths. The population with feasible paths is initialized with randomly generated paths. The fitness value is evaluated for the number of available candidate paths by applying objective functions for different objectives. Then the fitness criterion determines the paths which are to be passed to participate in the next generation. MRPS-MOGA is developed with the novelty of genetic algorithms such as tournament selection, ring crossover, and adaptive bit string mutation for discovering the optimal path. For the successive generations, the population is selected using the tournament. The genetic operator, crossover operator, is applied for swapping the input string to obtain offspring which is called ring crossover. Consequently, another GA operator mutation is carried out randomly on t

关键词： Mobile robot path planning Multiple objectives Meta-heuristic search Fitness Tournament selection Ring crossover adaptive bit string mutation

来源：评论

学校读者我要写书评

暂无评论

RETRACTED: Multi-objective genetic algorithm for mobile robot path planning in industrial automation (Retracted Article)

引用

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023年第4期44卷 6829-6842页

作者： Suresh, K. S. Ravichandran, K. S. Venugopal, S. SASTRA Deemed Univ Sch Comp Thanjavur Tamil Nadu India Natl Inst Technol Nagaland India

Due to the problem's high level of complexity, the optimization strategies used for the mobile robot path planning problem are quite expensive. The Mobile Robot Path Search based on a Multi-objective Genetic Algorithm (MRPS-MOGA) is suggested as a solution to the complexity. The MRPS-MOGA resolves path planning issues while taking into account a number of different factors, including safety, distance, smoothness, trip duration, and a collision-free path. In order to find the best approach, the suggested MRPS-MOGA takes into account five main objectives. The MOGA is used to pick the best path from a variety of viable options. Paths produced at random are used to initialise the population with viable paths. By using objective functions for various objectives, the fitness value is assessed for the quantity of potential candidate paths. In order to achieve diversity in the population, another GA operator mutation is carried out at random on the sequence. Once more, the individual fitness criterion is supported in order to derive the best path from the population. With various situations, an experimental research of the suggested MRPS-MOGA is conducted. The outcome shows that the suggested MRPS-MOGA performs better when choosing the best path with the least amount of time complexity. MRPS-MOGA is more effective than the currently used approaches, according to the experimental analysis.

关键词： Mobile robot path planning Multiple objectives meta-heuristic search Fitness tournament selection ring crossover adaptive bit string mutation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：