首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Optimization Complete Area Coverage by Reconfigurable hTrihex Tiling Robot
【2h】

Optimization Complete Area Coverage by Reconfigurable hTrihex Tiling Robot

机译:可重构hTrihex平铺机器人优化整个区域的覆盖范围

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Completed area coverage planning (CACP) plays an essential role in various fields of robotics, such as area exploration, search, rescue, security, cleaning, and maintenance. Tiling robots with the ability to change their shape is a feasible solution to enhance the ability to cover predefined map areas with flexible sizes and to access the narrow space constraints. By dividing the map into sub-areas with the same size as the changeable robot shapes, the robot can plan the optimal movement to predetermined locations, transform its morphologies to cover the specific area, and ensure that the map is completely covered. The optimal navigation planning problem, including the least changing shape, shortest travel distance, and the lowest travel time while ensuring complete coverage of the map area, are solved in this paper. To this end, we propose the CACP framework for a tiling robot called hTrihex with three honeycomb shape modules. The robot can shift its shape into three different morphologies ensuring coverage of the map with a predetermined size. However, the ability to change shape also raises the complexity issues of the moving mechanisms. Therefore, the process of optimizing trajectories of the complete coverage is modeled according to the Traveling Salesman Problem (TSP) problem and solved by evolutionary approaches Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Hence, the costweight to clear a pair of waypoints in the TSP is defined as the required energy shift the robot between the two locations. This energy corresponds to the three operating processes of the hTrihex robot: transformation, translation, and orientation correction. The CACP framework is verified both in the simulation environment and in the real environment. From the experimental results, proposed CACP capable of generating the Pareto-optimal outcome that navigates the robot from the goal to destination in various workspaces, and the algorithm could be adopted to other tiling robot platforms with multiple configurations.
机译:完整的区域覆盖计划(CACP)在机器人技术的各个领域(例如区域探索,搜索,营救,安全性,清洁和维护)中发挥着至关重要的作用。具有改变形状能力的平铺机器人是一种可行的解决方案,可以增强以灵活的尺寸覆盖预定义地图区域并访问狭窄空间限制的能力。通过将地图划分为与可变机器人形状相同大小的子区域,机器人可以将最佳运动计划到预定位置,将其形态转换为覆盖特定区域,并确保地图被完全覆盖。本文解决了最优导航规划问题,包括最小的形状变化,最短的行驶距离和最短的行驶时间,同时确保完全覆盖地图区域。为此,我们为带有三个蜂窝形状模块的名为hTrihex的平铺机器人提出了CACP框架。机器人可以将其形状转换为三种不同的形态,从而确保以预定大小覆盖地图。但是,改变形状的能力也提出了移动机构的复杂性问题。因此,根据旅行商问题(TSP)问题对优化全覆盖轨迹的过程进行建模,并通过进化方法遗传算法(GA)和蚁群优化(ACO)进行求解。因此,清除TSP中的一对航点的成本权重定义为机器人在两个位置之间所需的能量转移。该能量与hTrihex机器人的三个操作过程相对应:转换,平移和方向校正。 CACP框架已在仿真环境和实际环境中进行了验证。从实验结果来看,提出的CACP能够生成帕累托最优结果,该结果可在各种工作空间中将机器人从目标导航到目的地,并且该算法可用于具有多种配置的其他平铺机器人平台。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号