I. Structural Composition: The "Skeleton" and "Muscles" of the Robotic Arm
1. Joint: The core that rotates flexibly
Joints are the key to achieving multi-directional movement and are driven by motors or hydraulic systems. The six-axis robotic arm performs complex movements through six rotating joints (simulating the rotation of the shoulder, elbow, and wrist), each of which independently controls the Angle to ensure that the end effector (such as the gripper) precisely reaches the target position.
2. Drive System: The "engine" that provides power
Motor drive (mainstream solution): Micro motors directly drive the joints, featuring fast response and precise control (such as the six-axis robotic arm controlled by STM32).
Hydraulic/pneumatic drive: Hydraulic is suitable for heavy-load scenarios (such as heavy industry), while pneumatic is cost-effective but has limited precision (mostly used for simple grasping).
Shape memory alloy drive: Utilizing material properties to achieve flexible movement, suitable for lightweight prostheses or micro-robots.
3. Transmission System: The "bridge" for Transmitting Power
Tendon transmission: Designed to imitate human tendons, it transmits power through high-strength ropes and reduces the weight at the end (such as Tesla's Dexterous hand).
Connecting rod/gear transmission: The rigid structure has strong load-bearing capacity, but relatively low flexibility (mostly used in industrial grippers).

Ii. Control Principle: The "Brain" and "Perception" of Robotic Arms
1. Sensors: The "eyes" and "touch" for real-time monitoring
Position sensor: Monitors joint angles to ensure precise and accurate movement trajectories.
Force/torque sensor: Senses the operating force to prevent collision or damage to objects (such as precise control in medical surgeries)
Visual sensor: Identifying the shape and position of objects (such as locating goods in logistics sorting)
2. Control Algorithm: A "Decision System" for precise operation
Kinematic analysis: Plan the path through forward kinematics (calculating the end position given the joint Angle) and inverse kinematics (inferring the joint Angle given the target position).
Adaptive learning: Integrating machine learning algorithms to optimize control strategies based on task requirements (such as a six-axis robotic arm self-adjusting its grasping force).
PID control: A classic algorithm that achieves stable motion through proportional, integral, and differential regulation (such as motor speed control).
Iii. Movement Execution: "Action Realization from Planning to Implementation.
1. Trajectory Planning: The "design drawing" of the ideal path. The robotic arm first determines the spatial trajectory of the end effector (such as straight or curved movement) through "path generation", and then converts the trajectory into angular changes of each joint through inverse kinematics to ensure the continuity of the movement.
2. Feedback Adjustment: Real-time optimized "error correction mechanism" During movement, sensors continuously provide feedback on position, force and other information. The control system adjusts joint movements based on the data (such as decelerating to avoid collision and correcting grasping deviation) to ensure precise and safe final operation.
3. Typical scenario examples
Industrial assembly: The robotic arm moves parts along the preset trajectory, and the sensor detects the position deviation and makes real-time adjustments.

Medical surgery: The lesion is located through visual sensors, and the force of surgical instruments is controlled by force sensors to avoid tissue damage.

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