In the current era of rapid technological development, obstacle avoidance technology has become crucial for ensuring safety and efficient operation in numerous fields. From drones soaring in the sky to unmanned ships navigating the waves, and AGV carts flexibly shuttling in intelligent warehouses, these devices must accurately detect and avoid obstacles when operating autonomously in complex environments. Radar modules, with their exceptional performance, have emerged as the core of obstacle avoidance technology. Like the "intelligent eyes" of devices, they endow equipment with keen environmental perception, significantly expanding their application scope and enabling safer, more stable operation in complex scenarios.??
Advantages of Radar Modules for Obstacle Avoidance??
Strong Environmental Adaptability??
Compared with other obstacle avoidance sensors, radar modules demonstrate remarkable environmental adaptability. Whether in pitch-black night, scorching daylight, or harsh weather conditions like rain, fog, or sandstorms, radar can steadily perform its obstacle avoidance function. This is because radar relies on electromagnetic waves for detection, which are minimally affected by factors such as light and weather. For instance, in intelligent warehouse scenarios, AGV carts often work in dimly lit environments with possible dust. Here, radar modules can stably provide accurate obstacle information for AGVs, ensuring their efficient and safe operation—unlike some optical sensors that may misjudge or fail due to poor lighting or dust obstruction.??
High-Precision Detection??
Radar modules exhibit extremely high precision in distance and speed measurement, providing accurate data support for obstacle avoidance systems. Take millimeter-wave radar as an example: its distance resolution can reach centimeter-level, and its speed measurement accuracy is also remarkable. This high-precision detection capability allows devices to precisely sense the position and motion state of surrounding obstacles, laying a solid foundation for subsequent obstacle avoidance decisions. In the field of autonomous driving, radar systems installed in vehicles can accurately measure the distance and relative speed to preceding vehicles, pedestrians, and road obstacles, helping the vehicle adjust its driving speed and direction in a timely manner, effectively avoiding collisions and providing strong protection for driving safety.??
Good Real-Time Performance??
Radar modules can scan and detect the surrounding environment at extremely high frequencies, updating obstacle information in real time. This feature enables devices to respond rapidly to dynamically changing environments. For example, during a drone's mission, it may suddenly encounter a moving obstacle like a bird. At this time, the radar module, with its fast data update capability, can promptly capture the bird's position and speed changes, quickly transmit this information to the drone's control system, allowing the drone to make rapid evasive maneuvers, avoid danger, and ensure the smooth completion of the flight mission.??
Applications of Radar Modules in Obstacle Avoidance Across Different Fields??
UAV Field??
In the development of UAV technology, obstacle avoidance technology plays a pivotal role. As the core component of UAV obstacle avoidance systems, radar modules have made significant contributions to safe flight. Take the millimeter-wave radar obstacle avoidance module for fixed-wing UAVs launched by Zhihang as an example: it operates at a frequency of 24GHz, with a maximum measurement distance of 200m and a measurement accuracy of better than 2cm. When a fixed-wing UAV is flying, the flight controller detects obstacles at a frequency of 10Hz. Once an obstacle meeting specific requirements is found, the UAV can autonomously respond with preset obstacle avoidance behaviors, such as hovering, returning, or landing, while promptly notifying the operator through the ground control station. Moreover, this radar uses an intelligent filtering algorithm to automatically filter out interference data from birds, small targets, etc., effectively preventing false triggers and greatly improving UAV flight safety. During the operation of agricultural plant protection UAVs, there may be obstacles like utility poles and trees in the fields. Millimeter-wave radar can accurately detect these obstacles, helping UAVs avoid them skillfully and ensuring the efficient and safe execution of pesticide spraying tasks.??
Unmanned Ship Field??
Unmanned ships navigating in complex water environments face challenges from various obstacles, such as reefs, buoys, and other vessels. Radar sensor modules play a key role in unmanned ship obstacle avoidance systems. For example, in some unmanned ship projects, the selected radar sensor modules have strong environmental adaptability, are unaffected by light, and can quickly measure obstacle distances. Meanwhile, combined with infrared sensor modules to obtain obstacle position information, this data is transmitted to a Raspberry Pi controller for analysis and then displayed on an upper Android terminal screen, enabling users to monitor the unmanned ship's operation in real time. By operating control buttons on the upper computer screen, users can control motor speed, change the unmanned ship's driving trajectory, and achieve automatic obstacle avoidance. In tasks such as maritime military patrols and rescuing drowning personnel, unmanned ships rely on the obstacle avoidance function of radar modules to safely navigate in complex water environments and accurately execute missions.??
Intelligent Warehouse Field??
In intelligent warehouses, AGV carts need to travel quickly and accurately in narrow passages and among dense shelves while avoiding collisions with shelves, other AGVs, and staff. Lidar performs excellently in AGV obstacle avoidance applications. Take the Benewake lidar as an example: its single-point定向 (directional) obstacle avoidance module is based on the ToF (Time of Flight) principle, used for short-range obstacle detection and avoidance within 0.1m to 12m. The module has a small field of view and good collimation to avoid false triggers, with a data refresh rate as high as 100–1000Hz, enabling sensitive obstacle detection and providing accurate distance information for AGV systems to guide timely braking or deceleration commands. Solid-state 3D area array directional obstacle avoidance lidars, such as CE30, detect obstacle information within a fixed line-of-sight by emitting elliptical conical beams. With a high angular resolution of 1°, they can precisely identify obstacle positions and offer custom obstacle avoidance modes and secondary development obstacle avoidance modes. In the custom mode, they filter key obstacle avoidance targets for AGVs and provide distance information; the secondary development mode offers AGVs obstacle point cloud maps depicting rough outlines. Installing lidars in positions such as the front of warehouse AGVs, the front of forklift forks, or the front and rear of intelligent shuttle carts can real-time monitor obstacles, control vehicle deceleration or braking, and assist in rapid cargo storage/retrieval and intelligent handling, greatly improving warehouse logistics efficiency and safety.??
Robot Field??
In robot application scenarios, whether industrial robots performing precise operations on production lines or service robots moving autonomously in home and office environments, obstacle avoidance is a vital function. Lidar, as an important sensor for robots, can perform 360° scans of the surrounding environment and construct centimeter-level high-precision maps, providing strong support for obstacle avoidance and navigation. For example, some indoor service robots are equipped with lidar. During movement, they continuously scan the environment to obtain real-time obstacle position and distance information. When an obstacle is detected, the robot's control system plans a new path based on this information to bypass the obstacle and continue moving. Meanwhile, to better handle obstacle avoidance in complex environments, robots often use supplementary sensors, such as ultrasonic sensors. Although ultrasonic sensors have a relatively short detection range and limited 3D contour recognition accuracy, they are low-cost, easy to implement, and can identify transparent objects. Collaborating with lidar, they further enhance the reliability and accuracy of robot obstacle avoidance. In industrial automation production lines, robots use the fused information from radar modules and other sensors to move flexibly among complex equipment and materials, efficiently complete production tasks, and avoid collisions, ensuring stable production line operation.
