Design and Development of an Intelligent Quadruped Rescue Robot for Disaster Response

In recent years, intelligent robotic arms have attracted a lot of attention due to their precision and flexibility in automated tasks, especially in dynamic environments that require high-precision operation. Based on the existing model, this paper proposes an innovative system that integrates high-precision servo control, computer vision and optimized motion planning. The robotic arm uses six high-torque serial bus servos (25kg/cm, 0-300°), which are precisely controlled by independent IDs, and integrate RGB cameras with Jetson Nano to achieve “hand-eye collaboration” perception. The Aruco code distance estimation and inverse kinematics optimization algorithm are innovatively introduced to obtain the target position and attitude in real time, and accurately calculate the rotation angle of the joint. In addition, the combination of color filtering, target recognition and distance estimation improves the accuracy of autonomous grasping. Experimental results show that the model achieves high-precision and stable control in complex environments, and provides technical support for the application of intelligent robotic arms in the fields of industry, rescue and human-computer interaction.