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相关概念视频

Heuristics01:21

Heuristics

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Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
93
Problem-Solving01:29

Problem-Solving

165
Effective problem-solving consists of two steps: 1. identifying the problem and 2. selecting the appropriate problem-solving strategy (i.e., a plan of action used to find a solution). Humans use four problem-solving strategies:
165
The Availability Heuristic01:08

The Availability Heuristic

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A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
6.0K
Trial and Error and Algorithm01:12

Trial and Error and Algorithm

118
A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
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The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

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In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
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相关实验视频

Updated: Jul 5, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

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一种基于搜索战略的安全启发式路径规划方法.

Xiaozhen Yan1, Xinyue Zhou1, Qinghua Luo1,2

  • 1School of Information Science and Engineering, Harbin Institute of Technology at WeiHai, No. 2 Wenhua West Road, Weihai 264209, China.

Sensors (Basel, Switzerland)
|January 11, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了机器人新的启发式路径规划方法,提高了安全性和效率. 这种新方法显著改善了路径的平滑性,并减少了执行时间和长度,节省了机器人的电池功率.

关键词:
没有碰撞的安全安全.启发式听觉学是一种启发式听觉学.移动机器人 移动机器人最好的边界是最优的边界.路径规划路径规划路径规划

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相关实验视频

Last Updated: Jul 5, 2025

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 人工智能的人工智能
  • 计算机科学 计算机科学

背景情况:

  • 工业环境中的机器人路径规划受到安全,无碰撞和光滑轨迹的需求的挑战.
  • 现有的算法往往难以同时针对多个标准进行优化,导致低效或危险的路径.

研究的目的:

  • 开发一种安全的启发性路径规划方法,可以产生无碰撞,光滑的机器人路径,最小的拐点.
  • 在路径长度,执行时间和流性方面改进传统的路径规划算法,如A-star.

主要方法:

  • 一种新的搜索策略,扩展搜索节点并计算节点状态 (正常或危险).
  • 纳入"危险系数"来选择风险较低的路径.
  • 整合环境设施,以确定路径生成的最佳边界.

主要成果:

  • 与A星算法相比,路径长度减少了2.89%.
  • 执行时间缩短了13.98%.
  • 提高了93.17%的路径平滑性,从而使机器人导航更可靠.

结论:

  • 建议的启发式路径规划方法在安全性,效率和流性方面比传统算法有了显著的改进.
  • 优化的路径减少了功耗,延长了机器人的操作时间和电池寿命.
  • 这种方法使工业生产中的机器人能够更安全,更可靠地完成任务.