In the harsh on-site environment when sudden disasters such as earthquakes and mining accidents occur, the urgency and danger of rescue and search and rescue tasks highlight the urgent need for intelligent search and rescue robots. It is aimed at the situation that the search and rescue robot has difficulty walking in the narrow space of the ruins, and in the low-light environment, the image processing time is long and the details are lost. Firstly, the 3D model of the robot is designed based on bionics, and the motion of the robot is controlled; secondly, in order to improve the illumination consistency of the image in the search and rescue work, a structure-aware smooth model based on Retinex retina is added, which provides a high-quality search and rescue robot. The output can be seen, and an image evaluation model is established to eliminate low-quality images. Finally, the algorithm accelerates the solver to reduce the image processing time to meet the needs of real-time output of high-quality images on the Raspberry Pi. The experimental results show that when the hexapod robot works in a low-light environment, the image processing time of the Raspberry Pi is only 0.23 seconds, which greatly reduces the output delay, and the peak signal-to-noise ratio is 14.752 dB. It has great application prospects in future geological surveys, seismic searches, and difficult terrain detection.