Composite robots combine the functions of mobile robots (such as AGVs) and robotic arms, and are widely used in logistics, manufacturing, and other fields. Grasping accuracy is one of its core performance indicators, which directly affects work efficiency and product quality. This article will explore the influencing factors and improvement strategies of the grasping accuracy of composite robots.
1, Definition of gripping accuracy for composite robots
Grasping accuracy refers to the ability of end effectors (such as grippers, suction cups, etc.) of robots to accurately reach the target position and stably grasp objects while performing grasping tasks. Usually measured in millimeters (mm) or micrometers (µ m), the higher the accuracy, the stronger the robot's ability to adapt to complex tasks.
2, The main factors affecting grasping accuracy
1. Positioning accuracy of robotic arm
The joint accuracy, repetitive positioning accuracy, and rigidity of the robotic arm directly affect the grasping accuracy. High precision robotic arms typically use high-precision servo motors and reducers.
2. Accuracy of the visual system
Visual systems, such as 2D/3D cameras, are used to recognize the position and pose of target objects. The resolution, algorithm accuracy, and environmental lighting conditions of the camera can all affect the capture accuracy.
3. Design of end effector
The design of end effectors such as grippers and suction cups that are suitable for the shape, weight, and material of the target object directly affects the stability and accuracy of grasping.
4. Environmental factors
Environmental factors such as ground flatness, vibration, and temperature changes may affect the positioning and grasping accuracy of robots.
5. Performance of control system
The optimization level of the control algorithm, communication delay, and feedback speed of the sensor will all affect the grasping accuracy.
6. Object characteristics
The shape, size, surface material (such as smooth or rough), and placement posture (such as stacking or scattering) of the target object also pose challenges to grasping accuracy.
3, Strategies for improving grasping accuracy
1. Optimize the design of the robotic arm
Adopting high-precision servo motors and reducers to enhance the repetitive positioning accuracy of the robotic arm.
Enhance the rigidity of the robotic arm, reduce vibration and deformation.
2. Upgrade the visual system
Using high-resolution 3D cameras combined with deep learning algorithms to improve the recognition accuracy of target objects.
Optimize lighting conditions to reduce the interference of ambient light on the visual system.
3. Improve the end effector
Design specialized grippers or suction cups based on the characteristics of the target object to enhance the stability and accuracy of grasping.
Introduce force feedback technology to adjust the grasping force in real time, avoiding object sliding or damage.
4. Enhance environmental adaptability
Lay guide wires or QR codes on the ground to improve the positioning accuracy of mobile robots.
Use shock absorbers to reduce the impact of environmental vibrations on the robot.
5. Optimize control algorithms
Adopting advanced control algorithms such as PID control and fuzzy control to improve the motion accuracy of the robotic arm.
Reduce communication latency and ensure real-time feedback of sensor data.
6. Multi sensor fusion
Combining various sensor data such as visual, force, and tactile senses to enhance the intelligence level of the grasping process.
Real time correction of grasping path and force through sensor fusion technology.
7. Regular calibration and maintenance
Regularly calibrate the robotic arm, vision system, and sensors to ensure accuracy does not decrease over time.
Timely replace worn parts to maintain optimal performance of the robot.