防护热板法(guarded hot plate,GHP)是测量隔热材料导热系数最精确的方法,此方法的传统系统稳态判断方法耗时长,采用的时间间隔固定,导致整体测量时间较长.为了缩短测量时间,本文提出一种基于动态周期识别的系统稳态判断方法,对热板加...防护热板法(guarded hot plate,GHP)是测量隔热材料导热系数最精确的方法,此方法的传统系统稳态判断方法耗时长,采用的时间间隔固定,导致整体测量时间较长.为了缩短测量时间,本文提出一种基于动态周期识别的系统稳态判断方法,对热板加热功率进行卡尔曼平滑滤波和动态周期识别,变固定时间间隔为动态时间间隔,再对连续测量的4组导热系数进行判断,使其实时准确地反映系统的测量状态.利用此判断方法对绝热材料标准参比板的导热系数进行了测量,结果表明,测量时间缩短了大于25!,测量效率明显提高.展开更多
This paper presents a novel movement planning algorithm for a guard robot in an indoor environment, imitating the job of human security. A movement planner is employed by the guard robot to continuously observe a cert...This paper presents a novel movement planning algorithm for a guard robot in an indoor environment, imitating the job of human security. A movement planner is employed by the guard robot to continuously observe a certain person. This problem can be distinguished from the person following problem which continuously follows the object. Instead, the movement planner aims to reduce the movement and the energy while keeping the target person under its visibility. The proposed algorithm exploits the topological features of the environment to obtain a set of viewpoint candidates, and it is then optimized by a cost-based set covering problem. Both the robot and the target person are modeled using geodesic motion model which considers the environment shape. Subsequently, a particle model-based planner is employed, considering the chance constraints over the robot visibility, to choose an optimal action for the robot. Simulation results using 3D simulator and experiments on a real environment are provided to show the feasibility and effectiveness of our algorithm.展开更多
文摘防护热板法(guarded hot plate,GHP)是测量隔热材料导热系数最精确的方法,此方法的传统系统稳态判断方法耗时长,采用的时间间隔固定,导致整体测量时间较长.为了缩短测量时间,本文提出一种基于动态周期识别的系统稳态判断方法,对热板加热功率进行卡尔曼平滑滤波和动态周期识别,变固定时间间隔为动态时间间隔,再对连续测量的4组导热系数进行判断,使其实时准确地反映系统的测量状态.利用此判断方法对绝热材料标准参比板的导热系数进行了测量,结果表明,测量时间缩短了大于25!,测量效率明显提高.
文摘This paper presents a novel movement planning algorithm for a guard robot in an indoor environment, imitating the job of human security. A movement planner is employed by the guard robot to continuously observe a certain person. This problem can be distinguished from the person following problem which continuously follows the object. Instead, the movement planner aims to reduce the movement and the energy while keeping the target person under its visibility. The proposed algorithm exploits the topological features of the environment to obtain a set of viewpoint candidates, and it is then optimized by a cost-based set covering problem. Both the robot and the target person are modeled using geodesic motion model which considers the environment shape. Subsequently, a particle model-based planner is employed, considering the chance constraints over the robot visibility, to choose an optimal action for the robot. Simulation results using 3D simulator and experiments on a real environment are provided to show the feasibility and effectiveness of our algorithm.
