Low altitude unmanned aerial vehicles (usually referring to unmanned aerial vehicles flying at altitudes below 1000 meters) have undergone over a century of development, gradually evolving from early military remote-controlled aircraft to intelligent aircraft widely used in civilian fields today.
The starting point of the basic technology stage:
The origin of unmanned aerial vehicles and early low altitude flight control
The concept of drones can be traced back to the period of World War I. In 1918, the first radio operated small flying bomb, the "Kettering Bug," appeared and was considered the prototype of a cruise missile. However, due to poor accuracy and susceptibility to radio interference, the practical application of such drones has progressed slowly. After World War I, many countries used drones as target drones to train their air defense forces; After the end of World War II, some countries converted a large number of surplus military aircraft into unmanned remote control aircraft for tasks such as nuclear testing sampling. The demand for unmanned reconnaissance during the Cold War period drove new explorations in drone technology, resulting in the emergence of specially designed small tactical unmanned reconnaissance aircraft.
The advancement of electronic technology has increased the flexibility and importance of drones, and some countries have attempted to use manned aircraft to remotely control drones for precise attacks. However, due to the immaturity of remote navigation technology at that time, drones had bottlenecks in stable control and precise positioning. In the 1970s and 1980s, newly developed practical unmanned aerial vehicle systems such as the "Scout" emerged in the military. Overall, the technical features of this basic stage are: it solves the fundamental problem of drones being able to fly, but mainly relies on manual remote control and simple autopilot (such as gyroscope stabilization devices) to maintain flight, with limited flight control and endurance performance, and has not yet formed mature industrial applications.
Core technology evolution:
Key technological breakthroughs since the 1980s
Flight Control System (FLS): In the early days, the flight control of unmanned aerial vehicles was mainly achieved through wireless remote control and simple stabilizers, and the flight attitude was manually corrected in real time on the ground. Nowadays, flight control systems have developed into the "brain" of drones, integrating autopilot, multi-sensor data fusion, and intelligent control algorithms, enabling autonomous takeoff and landing, route following, and task execution. Modern flight control computers have greatly improved the stability and autonomy of drones, enabling them to maintain precise control of attitude and heading in complex environments. The introduction of artificial intelligence technology further endows flight control systems with autonomous learning and decision-making capabilities, promoting flight control from remote control to autonomous flight.
Navigation and positioning technology: Accurate positioning is a prerequisite for drones to complete tasks. Early drone navigation mainly relied on ground radio beacons or pure inertial navigation, with significant errors. The popularization of GPS global satellite positioning in the mid-1990s was a milestone: since 1995, drones have been able to use satellite signals to determine their own position in real time, greatly improving navigation accuracy. After the completion of China's Beidou satellite navigation system, it has also been widely used in drone positioning, making positioning services more accurate and reliable, empowering new applications in fields such as power inspection. Modern drones typically integrate multi constellation GNSS (GPS, Beidou, etc.) and differential augmentation (RTK, etc.) to achieve centimeter level positioning, providing high-precision position support for autonomous flight and formation.
Communication link: The communication link has undergone a huge leap from analog to digital. In the early days, there were only narrowband analog remote control signals, with limited control distance and anti-interference ability. Nowadays, digital radio, private network communication, and even cellular networks (4G/5G) have been introduced into drone communication. Especially with the low latency and high bandwidth characteristics of 5G, beyond line of sight communication has become a reality: by deeply integrating navigation systems with 5G-A networks, unmanned aerial vehicles have successfully achieved long-distance beyond line of sight flight, breaking through traditional line of sight limitations. A highly reliable broadband communication network ensures the precision and safety of unmanned aerial vehicles flying beyond line of sight, avoiding risks such as position deviation caused by delays. This enables drones to receive remote commands, transmit high-definition image data in real-time, and support collaborative communication among cluster drones.
Energy and Power Systems: The advancement of energy technology has directly extended the endurance of drones. Traditional drones often use fuel engines or inefficient batteries, resulting in limited flight time. In recent years, the application of high-performance lithium batteries and brushless motors has led to the flourishing development of small electric multi rotor unmanned aerial vehicles. The continuous improvement of battery energy density, coupled with high motor efficiency and simple maintenance, has contributed to the prosperity of consumer grade drones. At the same time, the industry is actively exploring green energy, such as the experimental application of hydrogen fuel cells on large fixed wing unmanned aerial vehicles, which significantly improves flight time and reduces carbon emissions. In the future, with the advancement of battery technology and new energy, low altitude drones will achieve longer range and better environmental performance.
Obstacle avoidance and environmental perception: Early drones had almost no obstacle avoidance ability, high flight risks, and needed to operate in open environments. Nowadays, obstacle avoidance and perception technology have become key links in the automation and intelligence of drones. The autonomous obstacle avoidance system of unmanned aerial vehicles has roughly gone through three stages: perceiving obstacles, bypassing obstacles, modeling the environment, and autonomously planning paths. To achieve the above functions, various sensors are integrated and applied: ultrasonic ranging is used for close range detection, with mature technology but limited effective range; Infrared/laser ranging (TOF) expands the detection range and can obtain the distance and partial contour of obstacles; Binocular vision simulates the principle of human eyes to obtain depth information and achieve three-dimensional perception of obstacles; Combined with high-precision electronic maps, drones can also have advance knowledge of terrain and no fly zones. The integration of these obstacle avoidance perception technologies makes it possible for drones to autonomously fly in complex environments, significantly reducing collision accident rates, and has gradually become a standard feature for mid to high end drones.
Future trend prediction:
Technology integration, intelligent clusters, and green innovation
Multi technology integration empowers the intelligence of unmanned aerial vehicles. Artificial intelligence (AI), 5G communication, new navigation and positioning technologies will be deeply integrated into drones to form an "intelligent flight" system. On the one hand, AI will endow drones with stronger environmental perception and autonomous decision-making capabilities - by using onboard neural networks to identify targets, plan paths, optimize flight control in real-time, enabling drones to autonomously execute tasks even in complex dynamic environments. On the other hand, 5G-A/6G network provides communication support of "large bandwidth+low latency", which can realize real-time interaction and edge computing between UAV and cloud AI platform, and accelerate the iteration and deployment of intelligent algorithms. At the same time, the new generation of communication networks can also provide high-precision location services (combined with Beidou positioning enhancement), further improving the reliability of drone navigation.
Intelligent clustering and collaborative work. The multi machine collaborative drone swarm (swarm) technology is considered a disruptive technological direction. Drone clusters, through networking communication and swarm intelligence algorithms, can enable numerous drones to collaborate like a "swarm" to complete tasks such as large-scale area searches, formation performances, and saturation attacks. Intelligent clustering requires solving a series of technical difficulties such as cluster communication protocols, autonomous task allocation, and cluster collision avoidance. At present, researchers have proposed a multi-layer cluster control scheme inspired by swarm intelligence, which enables drone swarms to autonomously divide labor, avoid collisions, and collaborate to complete tasks.
Automated unmanned systems and operational systems. Drones are moving from a single product to a systematic and automated unmanned system. The future unmanned aerial vehicle system will cover the full process automation of autonomous takeoff and landing, charging maintenance, task scheduling, and data processing. For example, the "drone honeycomb" apron with automatic battery replacement or charging is being developed, allowing drones to perform tasks 24 hours a day without human supervision. The unmanned aerial vehicle traffic management (UTM) system will automatically coordinate the flight plans of a large number of drones to prevent aerial conflicts. The concept of autonomous intelligent unmanned systems is to complete complex tasks without or with minimal human intervention, which requires the integration of digital twins, robotics technology, and artificial intelligence. A typical autonomous logistics drone system in an unmanned warehouse can autonomously perceive the environment, collaborate with other robots, and operate efficiently through cloud scheduling. In the future, there may be a dedicated unmanned aerial vehicle (UAV) operation network in the low altitude field: automated ground stations and cloud platforms will interface with user needs to intelligently schedule airborne UAV resources. This highly automated operation system will greatly reduce labor costs, enabling drones to truly achieve "on-demand operation", and also placing higher demands on network security and system reliability.
Lightweight aircraft and green energy. Under the trend of environmental protection and sustainable development, low altitude aircraft will pay more attention to lightweight design and the use of clean energy. The advancement of materials science, such as new carbon fiber composite materials and 3D printed structures, will continue to reduce the weight of unmanned aerial vehicles, improve load capacity and energy efficiency. Reducing weight not only extends flight time, but also lowers the risk of crashes and manufacturing costs, which is beneficial for the widespread adoption of drones. In terms of power, "green" will become the keyword - electrification is the trend, small multi rotor aircraft are almost fully powered by batteries, and in larger drones, clean energy solutions such as hydrogen fuel cells and solar cells are making progress. With the maturity of hydrogen fuel cell technology, hybrid unmanned aerial vehicles (such as fuel/electric hybrids, hydrogen electric hybrids, etc.) may emerge, balancing long endurance and high power output. In addition, battery recycling and noise reduction design will also be included in green assessment indicators to ensure the ecological sustainability of the drone industry.
Upgrading industry standards and safety supervision. In the face of new challenges brought by intelligence and clustering, it is necessary to develop unmanned aerial vehicle air traffic rules, data security standards, and ethical norms for AI decision-making in the future. Regulatory authorities may use 5G and Beidou to establish a low altitude monitoring network, achieving real-time monitoring and control of drones, "making low altitude aircraft visible, audible, and manageable". In addition, anti drone technology will also develop synchronously to address the threat of "black flight" and ensure low altitude space security.
