Implementing autonomous perception and obstacle avoidance for robots, with diverse sensing options

With the rapid development of technology, robots have taken on the role of capable assistants in many industries. Whether it is the production and consumption services on industrial production lines, or the companionship in daily life, robots are taking on more tasks and playing a more important role.

In order to enable robots to efficiently and safely complete tasks, the perception and obstacle avoidance process is particularly crucial. In fact, there are already many types and quantities of sensors applied in traditional robots, including key data provided by sensors in terms of pressure, temperature, speed, and so on. With the upgrading and replacement of robots, the ability of robots to perceive and avoid obstacles is becoming increasingly important.

Implementing autonomous perception and obstacle avoidance for robots
The obstacle avoidance function of robots is based on the ability to perceive the surrounding environment. After perception, data processing and analysis reflect the robot's ability to perceive and avoid obstacles during autonomous movement. The completeness of this function is directly related to the operational efficiency and safety of the robot. A robot with efficient obstacle avoidance function can freely navigate through various environments without human intervention, not only greatly improving work efficiency, but also significantly reducing potential damage and malfunctions caused by collisions, ensuring the robot's longevity and destiny.

Taking the industrial field as an example, there are many solutions for robot obstacle avoidance, including but not limited to ultrasonic obstacle avoidance, infrared obstacle avoidance, laser obstacle avoidance, visual obstacle avoidance, and so on. As is well known, ultrasonic and infrared solutions have relatively low overall costs, so they are also widely used in industrial robots.

Ultrasonic obstacle avoidance has good recognition for solid obstacles and transparent surfaces. Even in environments filled with smoke, ultrasonic waves can still detect objects in the environment very well. The sensing response of infrared technology is fast and the cost is also very low. It is now able to effectively distinguish detection signals from interference signals, and the drawbacks of nonlinearity and dependence on target reflectivity have also made significant progress compared to before.

Radar technology, as a cost-effective sensing method, is mature and widely applicable in detection, tracking, and positioning functions, and is also widely used in robots. In robot applications, medium to long range radar is generally more common. Nowadays, millimeter wave radar sensing is also being applied in robot perception and obstacle avoidance. This perception is less affected by environmental conditions and has a significant effect in outdoor movement and robot applications in black light automated factories.
In addition, its high precision and resolution can make more dense point cloud detection of detected objects, and the collected point information density can provide high fidelity. This clear obstacle avoidance data collection is a very important decision-making basis for mobile robots to avoid obstacles, and sufficient reliable data also ensures the improvement of robot autonomy.

Laser chip applied to robot obstacle avoidance
Laser obstacle avoidance is widely used in the field of robotics. Although the cost may be slightly higher, it can achieve more accurate and consistent obstacle avoidance effects, providing higher recognition and better consistency to the system. Both edge emitting laser EEL and vertical cavity surface emitting laser chip VCSEL have many applications.

EEL has advantages in high power density and high pulse power, and this light source technology is also stable under ambient light with slightly lower temperature drift. VCSEL is also very stable under ambient light, with more stable temperature drift. It is also characterized by high power scalability and can be used for devices of different power levels. In addition, its beam quality is relatively higher than EEL.

Laser technology has brought high added value to perception obstacle avoidance design, and the more uniform light spot of laser technology makes the image quality higher; The extremely narrow spectral bandwidth makes it more stable under ambient light and reduces temperature drift; More stable characteristics under high temperatures, suitable for design in more application scenarios; The bandwidth of high-speed switching provides a higher design upper limit, which can support high-frequency debugging, and the most typical application is in the ToF aspect.

Among the many technological routes of LiDAR, each light source has its suitable application scenario. In addition to considering the characteristics and basic requirements of LiDAR, it is also necessary to start from user needs. The first thing to consider is what kind of LiDAR different robots need, as well as the scanning method from mechanical rotation to MEMS and then to all solid state.

The perception and obstacle avoidance ability of robots is their core competitiveness, and every function such as perception, positioning, drawing, navigation, recognition, and obstacle avoidance cannot be separated from accurate environmental data collection. Numerous sensor components provide the robot system with as detailed environmental data as possible. In the future, these sensors will be further integrated and combined with ML inference to achieve deep environmental analysis. The robot will also achieve real-time perception of any target around it.