Water is an essential part of the urban ecosystem and plays a vital role in alleviating urban heat island (UHI) problems. The contribution toward UHI mitigation made by bodies of water needs to be ascertained to establish waterfront thermal environment construction standards. In this study, the thermal environment of the waterfront space of Tianjin in the cold regions of China was the research object. Through a survey including 141 valid questionnaires and the field measurement of four typical waterfront spaces in Tianjin, the thermal demand characteristics of recreational use for the waterfront environment and the influence of water on microclimate are discussed, supplemented by results from low-altitude infrared remote sensing technology, which was mainly used to obtain a wider range of infrared thermal images with higher accuracy. To improve the urban heat island effect and the quality of the ecological environment, this paper used outdoor thermal environment simulation software to quantitatively analyze the thermal environmental impact of outdoor public activity spaces around the representative urban body of water and proposes the optimization scheme of the waterfront space’s thermal environment. The results show that, based on the factors of water itself, the most economical water width was 70–80 m, and the cooling effect intensity of water had an essential correlation with the distance between the measured site and the water center. In terms of the environmental factors around the water, when the green lawn of the waterfront space was 12 m and the water shore’s geometric form was S-shaped, this could improve the cooling effect of water significantly. Waterfront activity spaces should focus on thermal comfort on the east and south water shores. It is expected that this study could provide practical implications and useful guidance for the planning and design of urban waterfront space in China’s cold regions.
Real-time and drift-free state estimation is essential for the flight control of Micro Aerial Vehicles (MAVs). Due to the vibration caused by the particular flapping motion and the stringent constraints of scale, weight, and power, state estimation divergence actually becomes an open challenge for flapping wing platforms’ longterm stable flight. Unlike conventional MAVs, the direct adoption of mature state estimation strategies, such as inertial or vision-based methods, has difficulty obtaining satisfactory sensing performance on flapping wing platforms. Inertial sensors offer high sampling frequency but suffer from flapping-introduced oscillation and drift. External visual sensors, such as motion capture systems, can provide accurate feedback but come with a relatively low sampling rate and severe delay. This work proposes a novel state estimation framework to combine the merits from both to address such key sensing challenges of a special flapping wing platform—micro flapping wing rotors (FWRs). In particular, a cross-fusion scheme, which integrates two alternately updated Extended Kalman Filters based on a convex combination, is proposed to tightly fuse both onboard inertial and external visual information. Such a design leverages both the high sampling rate of the inertial feedback and the accuracy of the external vision-based feedback. To address the sensing delay of the visual feedback, a ring buffer is designed to cache historical states for online drift compensation. Experimental validations have been conducted on two sophisticated microFWRs with different actuation and control principles. Both of them show realtime and drift-free state estimation.
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