Personnel Tracking Vision System
A safe, automated rig can only be achieved by tracking the locations of all people on the rig floor at all times.
New generation rigs commonly include pipe-handling and mechanized rig-floor equipment. For the time-being, person-machine-interactions are controlled solely by the equipment operator and increasing rig autonomous action represents a major safety concern.
Many wearable technologies exist for determining the location of personnel (e.g., RFID), and on-board protocols are designed to make sure personnel are not in harm’s way. However, both of these approaches require personnel compliance with protocols and voluntary usage of additional hardware, some of which may fail. Research in the application of personnel tracking and localization (Personnel Video Monitoring, or PVM) in various real-world scenarios is ongoing. The ongoing work has resulted in a prototype real-time system capable of accurate personnel location identification localization in a wide array of environments, against complicated backgrounds.
The PVM system leverages multiple camera feeds to simultaneously find the people in each frame (camera field of view). Then, using knowledge about the camera positions and orientations, each person’s location can be triangulated in rig coordinates, building a real-world spatial map of each person and his or her location. As people enter and exit the scene (work area), they appear as dots on a 2-dimensional map of the rig floor; the information in that map can then be automatically leveraged to inhibit automated equipment actions when people are in harm’s way.
Less rigorous personnel detection approaches often fail under complicated lighting, background and partial occlusion situations, and significant effort is required to ensure that the system is robust to these scenarios. Our technologies leverage state-of-the-art computer vision person detection algorithms, and are robust to widely varying lighting and complicated backgrounds. Furthermore, leveraging multiple cameras simultaneously allows PVM to track people even when they are occluded in several camera views.