Abstract
In refinery, petrochemical, and chemical plants, process technicians collect uncontaminated samples to be analyzed in the quality control laboratory all time and all weather. This traditionally manual operation not only exposes the process technicians to hazardous chemicals, but also imposes an economical burden on the management. The recent development in mobile manipulation provides an opportunity to fully automate the operation of sample collection. This paper reviewed the various challenges in sample collection in terms of navigation of the mobile platform and manipulation of the robotic arm from four aspects, namely mobile robot positioning/attitude using global navigation satellite system (GNSS), vision-based navigation and visual servoing, robotic manipulation, mobile robot path planning and control. This paper further proposed solutions to these challenges and pointed the main direction of development in mobile manipulation.
Highlights
Sample collection is crucial to plant performance, and this practice is widely used in refinery, petrochemical and chemical plants to monitor and confirm unit operation
This paper is to discuss these various challenges faced by mobile manipulation for sample collection in industrial environments in terms of control and path planning, localization, visual-based navigation and visual servoing, and robotic manipulation
We propose to automate this operation of sample collection using a mobile manipulator consisting of a mobile base and an industrial robotic arm
Summary
Sample collection is crucial to plant performance, and this practice is widely used in refinery, petrochemical and chemical plants to monitor and confirm unit operation. In the 1990s, the application of mobile manipulation went beyond the structured industrial environments and made its way into less structured human environments Khatib and his colleagues developed the Stanford Robotic Platform consisting of an omni-directional base and a Puma 560 robotic arm, an upper sonarring, and a lower sonar ring. Mobile manipulators for sample collection will have to travel from the lab to the plant via a shared path with pedestrians and other vehicles and performing sample collection under natural lighting conditions regardless day time and night time This full-weather all-time operation poses substantial challenges to the current technology of mobile manipulation. This paper is to discuss these various challenges faced by mobile manipulation for sample collection in industrial environments in terms of control and path planning, localization, visual-based navigation and visual servoing, and robotic manipulation. We shall discuss the challenges faced by control and path planning, GNSS, Lidar and stereo computer vision, and manipulation and propose our solutions
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