论文标题

使用启发式方法优化摇滚乐机制

Optimization of Rocker-Bogie Mechanism using Heuristic Approaches

论文作者

Senjaliya, Harsh, Gajjar, Pranshav, Vaghasiya, Brijan, Shah, Pooja, Gujarati, Paresh

论文摘要

在动态地形和环境中,最佳的运动和有效遍历外星漫游器是行星科学和地球物理系统领域的重要问题陈述。为行星流浪者的悬架机理设计最高级有效的体系结构是迈向健壮的流浪者的关键步骤。本文重点介绍了摇杆转型机制,这是一种与外国地形相关的标准悬架方法。在审查了可用的先前文献并利用各种优化和全局最小化算法之后,本文提供了一项有关流浪者悬架机制的机械设计优化的新研究。本文对模拟退火,遗传算法,群智能技术,盆地希望和差异进化进行了广泛的测试,同时彻底评估了每个相关的超级参数,以找到效用驱动的解决方案。我们还评估了上述任务的双重退火和子公司算法,同时保持了道德研究的无偏测试角度。计算效率和整体适应性被认为是评估相关算法的关键效率参数,也将重点放在可变输入种子中,以找到最合适的效用驱动策略。在经验上获得了模拟退火,它是表现最佳的启发式策略,其适合度为760,其优于其他算法,并在各种输入种子和个人性能指标上提供了一致的性能。

Optimal locomotion and efficient traversal of extraterrestrial rovers in dynamic terrains and environments is an important problem statement in the field of planetary science and geophysical systems. Designing a superlative and efficient architecture for the suspension mechanism of planetary rovers is a crucial step towards robust rovers. This paper focuses on the Rocker Bogie mechanism, a standard suspension methodology associated with foreign terrains. After scrutinizing the available previous literature and by leveraging various optimization and global minimization algorithms, this paper offers a novel study on mechanical design optimization of a rovers suspension mechanism. This paper presents extensive tests on Simulated Annealing, Genetic Algorithms, Swarm Intelligence techniques, Basin Hoping and Differential Evolution, while thoroughly assessing every related hyper parameter, to find utility driven solutions. We also assess Dual Annealing and subsidiary algorithms for the aforementioned task while maintaining an unbiased testing standpoint for ethical research. Computational efficiency and overall fitness are considered key valedictory parameters for assessing the related algorithms, emphasis is also given to variable input seeds to find the most suitable utility driven strategy. Simulated Annealing was obtained empirically to be the top performing heuristic strategy, with a fitness of 760, which was considerably superior to other algorithms and provided consistent performance across various input seeds and individual performance indicators.

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