<p>Robotic systems have the ability to perform industrial inspection tasks through the integration of visual and chemical servoing functions. A commonly used system is the image-based servoing system. This study presents an innovative approach that merges chemical servoing with visual defect detection in industrial settings using a hexapod robot. The main goal is to develop a hexapod robot capable of detecting and approaching a gas source through chemical servoing, and subsequently analyzing the source using a pretrained YOLOv5m model, a one-stage CNN detector architecture. The effectiveness of the proposed methodology is showcased through simulations that compare different chemical servoing algorithms and image defect detection techniques for gas source identification. In addition, a prototype of the hexapod robot is presented. </p>