Research Progress and Prospects of Agricultural Aero-Bionic Technology in China
Abstract
:1. Introduction
2. Biological Perception and Agricultural Aviation
2.1. Echolocation and Obstacle Avoidance
2.2. Binocular Stereo Vision Bionics
2.3. Compound Eye Bionics
3. Biological Behavior and Agricultural Aviation
3.1. Ant Colony Optimization
3.2. Particle Swarm Optimization
3.3. Genetic Algorithm
4. Biological Intelligence and Agricultural Aviation
4.1. Brain-Like Navigation
4.2. Convolutional Neural Network
5. Discussion
- Research on multiple bionic targets. In the complex and harsh farmland environment, aviation operations are usually faced with multiple complex problems. While a single bionic target provides an optimized solution to a specific problem, it also has limitations. Only by effectively realizing these goals can the optimal bionic design requirements be better achieved. For example, in the face of complex farmland operating environments in the future, a variety of combinations can be proposed for different sensor characteristics so that agricultural aircraft can cope with complex operating environments and achieve real-time obstacle avoidance requirements, and it can also provide feasibility for the realization of precision spraying and intelligent navigation for agricultural aircraft. A variety of fusion bionic algorithms can propose optimal solutions for farmland environments with different operating requirements, avoiding the problems of slow calculations and ease of falling into local optima in a single algorithm. At the same time, according to the different characteristics of each algorithm, a more optimized bionic fusion algorithm can be designed according to the types of farmland operation and existing problems in the future. Therefore, the fusion of multiple bionic designs will help to efficiently solve the technical problems faced in the field of agricultural aviation.
- In-depth exploration of three-dimensional spatial information. Three-dimensional spatial information exploration is mainly used in the fields of UAV obstacle avoidance, path planning, and image acquisition. When an aircraft faces complex and changeable operating environments such as terrain and air obstacles, the problem of how to effectively identify obstacles and make correct obstacle avoidance decisions still needs to be resolved. In China, there is relatively little research on the three-dimensional space operation of agricultural aircraft, and the follow-up work should increase the relevant research on the three-dimensional space operation of agricultural aviation.
- Research on miniaturization, integration, and intelligence of sensor devices. In the face of a harsh operating environment, the operational efficiency of agricultural aircraft is inseparable from the support of communication, navigation, command, and other sensor equipment in the aircraft. At present, in the Chinese agricultural aviation aircraft, sensor equipment can complete the work of information collection and communication of the operating environment. However, the function of the sensor is relatively single, and the product has a large gap with biological perception in terms of power consumption, volume, and anti-interference in a complex environment. Therefore, in the future, it is necessary to improve the equipment manufacturing process, combine with bionic technology, strengthen the development of miniaturized sensor devices, and conduct in-depth research on integrated and intelligent sensor devices.
- In-depth research on the mechanism of animal brain systems. Poor operating environment, electromagnetic interference, weak signal, and other factors usually affect the operating efficiency of agricultural aircraft, and even make it impossible to operate. Intelligent positioning and navigation technology obtains the surrounding environment information by imitating the mechanism of an animal brain system to construct cognitive maps or deep learning, so as to achieve the purpose of autonomous navigation and image recognition without relying on communication equipment. Agricultural aviation research on animal brain systems mainly focuses on deep learning, intelligent navigation, etc., but the current research is still at the theoretical stage, mainly because human beings have not yet fully understood the brain structure of animals, and the principle of cooperation between various cells and neurons in the brain needs to be further explored. In recent years, the combination of animal brain bionic research and robot learning has gradually become a new development trend, which provides a direction for the future intelligent development of agricultural aviation.
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Technology | Application | Advantage | Disadvantage | Maximum Distance | Research Hotspots in Agricultural Aviation |
---|---|---|---|---|---|
Ultrasonic | Ranging, obstacle avoidance | Low cost | Easy to be interfered by harsh environment, poor accuracy for long-distance detection | <10 m | Short-distance combined obstacle avoidance system |
Binocular stereo vision | Ranging, obstacle avoidance, image acquisition | Fast measurement, high resolution at close range | Illumination and harsh environment affect matching accuracy | <100 m | Optimize stereo matching algorithm and fusion algorithm |
Compound eyes | Image acquisition, obstacle avoidance | Large field-of-view, high sensitivity, fast measurement, high resolution | Vulnerable to harsh environment, imperfect technological development at present | <100 m | Camera array, curved array |
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Zhang, Y.; Tian, H.; Huang, X.; Ma, C.; Wang, L.; Liu, H.; Lan, Y. Research Progress and Prospects of Agricultural Aero-Bionic Technology in China. Appl. Sci. 2021, 11, 10435. https://doi.org/10.3390/app112110435
Zhang Y, Tian H, Huang X, Ma C, Wang L, Liu H, Lan Y. Research Progress and Prospects of Agricultural Aero-Bionic Technology in China. Applied Sciences. 2021; 11(21):10435. https://doi.org/10.3390/app112110435
Chicago/Turabian StyleZhang, Yali, Haoxin Tian, Xinrong Huang, Chenyang Ma, Linlin Wang, Hanchao Liu, and Yubin Lan. 2021. "Research Progress and Prospects of Agricultural Aero-Bionic Technology in China" Applied Sciences 11, no. 21: 10435. https://doi.org/10.3390/app112110435
APA StyleZhang, Y., Tian, H., Huang, X., Ma, C., Wang, L., Liu, H., & Lan, Y. (2021). Research Progress and Prospects of Agricultural Aero-Bionic Technology in China. Applied Sciences, 11(21), 10435. https://doi.org/10.3390/app112110435