Urban Comprehensive Carrying Capacity(UCCC)can describe the development of a city and is an important guarantee for its sustainable development.Production-Living-Ecological Space(PLES)is an important guideline for the...Urban Comprehensive Carrying Capacity(UCCC)can describe the development of a city and is an important guarantee for its sustainable development.Production-Living-Ecological Space(PLES)is an important guideline for the optimal development of China's land space in the new era.Based on the PLES,we construct a UCCC index system and analyzed the spatial and temporal distribution characteristics of the UCCC of each city in Zhejiang Province from 2006 to 2020.In addition,a coupling coordination degree model and an obstacle degree model are introduced to analyze the coupling coordination degree of the development of PLES of each city and the main constraint indicators,respectively,and a GM(1,1)model is used to predict the UCCC of each city in Zhejiang Province from 2021 to 2025.The study indicates that(1)the UCCC of each city is steadily increasing,with a growth rate of over 30%in 15 years.(2)As of 2020,the highest degree of coupling coordination reaches only 0.508,and it remains a major challenge for cities to improve the coordination degree of land use.(3)Some production space and living space indicators are the main obstacle indicators hindering the development of the UCCC in Zhejiang Province.(4)The forecast results show that the UCCC in each city will still maintain an upwards trend in the following 6 years and will gradually reach a high carrying capacity level.展开更多
Miniature jumping robots(MJRs)have difficulty executing autonomous movements in unstructured environments with obstacles because of their limited perception and computing resources.This study investigates the obstacle...Miniature jumping robots(MJRs)have difficulty executing autonomous movements in unstructured environments with obstacles because of their limited perception and computing resources.This study investigates the obstacle detection and autonomous stair climbing methods for MJRs.We propose an obstacle detection method based on a combination of attitude and distance detections,as well as MJRs’motion.A MEMS inertial sensor collects the yaw angle of the robot,and a ranging sensor senses the distance between the robot and the obstacle to estimate the size of the obstacle.We also propose an autonomous stair climbing algorithm based on the obstacle detection method.The robot can detect the height and width of stairs and its position relative to the stairs and then repeatedly jump to climb them step by step.Moreover,the height,width,and position are sent to a control terminal through a wireless sensor network to update the information regarding the MJR and stairs in a control interface.Furthermore,we conduct stair detection,modeling,and stair climbing experiments on the MJR and obtain acceptable precisions for autonomous obstacle negotiation.Thus,the proposed obstacle detection and stair climbing methods can enhance the locomotion capability of the MJR in environmental monitoring,search and rescue,etc.展开更多
基金supported by the National Natural Science Foundation of China[grant number 42071429]the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources[grant number KF-2023-08-19].
文摘Urban Comprehensive Carrying Capacity(UCCC)can describe the development of a city and is an important guarantee for its sustainable development.Production-Living-Ecological Space(PLES)is an important guideline for the optimal development of China's land space in the new era.Based on the PLES,we construct a UCCC index system and analyzed the spatial and temporal distribution characteristics of the UCCC of each city in Zhejiang Province from 2006 to 2020.In addition,a coupling coordination degree model and an obstacle degree model are introduced to analyze the coupling coordination degree of the development of PLES of each city and the main constraint indicators,respectively,and a GM(1,1)model is used to predict the UCCC of each city in Zhejiang Province from 2021 to 2025.The study indicates that(1)the UCCC of each city is steadily increasing,with a growth rate of over 30%in 15 years.(2)As of 2020,the highest degree of coupling coordination reaches only 0.508,and it remains a major challenge for cities to improve the coordination degree of land use.(3)Some production space and living space indicators are the main obstacle indicators hindering the development of the UCCC in Zhejiang Province.(4)The forecast results show that the UCCC in each city will still maintain an upwards trend in the following 6 years and will gradually reach a high carrying capacity level.
基金supported in part by the National Natural Science Foundation of China(61873066 and 62173090)the Zhi Shan Scholars Program of Southeast University,China(2242020R40096).
文摘Miniature jumping robots(MJRs)have difficulty executing autonomous movements in unstructured environments with obstacles because of their limited perception and computing resources.This study investigates the obstacle detection and autonomous stair climbing methods for MJRs.We propose an obstacle detection method based on a combination of attitude and distance detections,as well as MJRs’motion.A MEMS inertial sensor collects the yaw angle of the robot,and a ranging sensor senses the distance between the robot and the obstacle to estimate the size of the obstacle.We also propose an autonomous stair climbing algorithm based on the obstacle detection method.The robot can detect the height and width of stairs and its position relative to the stairs and then repeatedly jump to climb them step by step.Moreover,the height,width,and position are sent to a control terminal through a wireless sensor network to update the information regarding the MJR and stairs in a control interface.Furthermore,we conduct stair detection,modeling,and stair climbing experiments on the MJR and obtain acceptable precisions for autonomous obstacle negotiation.Thus,the proposed obstacle detection and stair climbing methods can enhance the locomotion capability of the MJR in environmental monitoring,search and rescue,etc.
