Evaluation of a Smart Mobile Robotic System for Industrial Plant Inspection and Supervision

Abstract

Automated and autonomous industrial inspection is a longstanding research field, driven by the necessity to enhance safety and efficiency within industrial settings. In addressing this need, we introduce an autonomously navigating robotic system designed for comprehensive plant inspection. This innovative system comprises a robotic platform equipped with a diverse array of sensors integrated to facilitate the detection of various process and infrastructure parameters. These sensors encompass optical (LiDAR, stereo, and ultraviolet (UV)/infrared (IR)/RGB cameras), olfactory (electronic nose), and acoustic (microphone array) capabilities, enabling the identification of factors such as methane leaks, flow rates, and infrastructural anomalies. The proposed system underwent individual evaluation at a wastewater treatment site within a chemical plant, providing a practical and challenging environment for testing. The evaluation process encompassed key aspects such as object detection, 3-D localization, and path planning, achieving an average precision (AP) of around 0.7662 in the 2-D object detection. In addition, specific evaluations were conducted for optical methane leak detection and localization, demonstrating the system’s capability to detect leaks as small as 40 mLmin-1. Furthermore, acoustic assessments focusing on pump equipment and gas leak localization yielded an absolute localization error of around 50 cm.