With the continuous advancement of industrial automation, robotic arms have become indispensable core equipment on production lines. However, in high-speed, high-density operational environments, risks of collisions between robotic arms and peripheral devices, workpieces, or even operators persist due to visual blind spots, positioning errors, or human intrusion. In the event of a collision, minor incidents may damage equipment and disrupt production, while severe cases can result in personal injuries. Therefore, establishing a comprehensive anti-collision monitoring system has become a critical component in ensuring the safe operation of smart manufacturing, with the collaborative application of various sensors serving as the "sensory nerves" of this system.

Force sensor: the "first responder" to collisions

Six-axis force/torque sensors are typically installed at the flange of a robot arm's end, capable of real-time detection of contact forces and torque changes in three-dimensional space. When the arm unexpectedly contacts an object, the sensor can detect abnormal forces within milliseconds, triggering the controller to halt or retract immediately, minimizing collision damage. Additionally, joint torque sensors monitor current and torque fluctuations in each joint motor, also identifying load variations to achieve indirect collision detection.

Proximity Sensor: The "Early Warning Radar" of Collisions

If the force sensor is a "post-event response," the proximity sensor achieves "pre-event prevention." Inductive proximity sensors are suitable for non-contact detection of metallic targets; capacitive sensors can detect both metallic and non-metallic objects; while ultrasonic and infrared sensors can detect the approach of personnel or obstacles within a certain range. By installing them at critical arm joints, a safety margin can be created before a collision occurs, allowing the control system to decelerate, avoid, or shut down in advance.

Visual Sensor: The "Eyes" of Global Situational Awareness

Industrial cameras and 3D vision sensors provide robots with global environmental perception capabilities. By capturing 3D point clouds of the workspace through depth cameras and LiDAR, combined with image recognition algorithms, the system can dynamically construct real-time maps of human-machine collaboration areas, identify worker positions and workpiece postures, and achieve dynamic path planning and collision prediction. The visual solution offers extensive coverage, compensating for the limited detection range of point-based sensors.

Multi-sensor Fusion: From Single Perception to Intelligent Protection

Each single sensor has its limitations: force sensors respond quickly but can only "after the fact" detect impacts, visual sensors have a broad range but are susceptible to lighting and occlusion, while proximity sensors are constrained by accuracy and distance. Modern impact prevention systems are moving toward multi-sensor fusion—constructing a peripheral warning layer with visual and proximity sensors, forming a contact response layer with force sensors and joint current monitoring, and then utilizing edge computing and AI algorithms to comprehensively analyze multi-source data, achieving a tiered protection strategy of "warning—deceleration—flexible contact—emergency stop.".

Conclusion

From force perception and proximity sensing to vision, advancements in sensor technology are transforming industrial robotic arms from "head-down labor" to "keen-eyed vigilance." The multi-sensor fusion anti-collision monitoring system not only significantly enhances production safety and equipment reliability but also lays a solid foundation for human-machine collaborative smart factories. In the future, with the deep integration of flexible tactile skin, MEMS sensors, and AI algorithms, robotic anti-collision monitoring will continue to evolve toward higher precision and greater adaptability, safeguarding smart manufacturing.