Date of Graduation
Master of Science in Industrial Engineering (MSIE)
Second Committee Member
W. Art Chaovalitwongse
Automation, Collaborative Robotics, Flexible Automation, Human-Machine Interface, Path Planning
Implementation of automated robotic solutions for complex tasks currently faces a few major hurdles. For instance, lack of effective sensing and task variability – especially in high-mix/low-volume processes – creates too much uncertainty to reliably hard-code a robotic work cell. Current collaborative frameworks generally focus on integrating the sensing required for a physically collaborative implementation. While this paradigm has proven effective for mitigating uncertainty by mixing human cognitive function and fine motor skills with robotic strength and repeatability, there are many instances where physical interaction is impractical but human reasoning and task knowledge is still needed. The proposed framework consists of key modules such as a path planner, path simulator, and result simulator. An integrated user interface facilitates the operator to interact with these modules and edit the path plan before ultimately approving the task for automatic execution by a manipulator that need not be collaborative. Application of the collaborative framework is illustrated for a pressure washing task in a remanufacturing environment that requires one-off path planning for each part. The framework can also be applied to various other tasks, such as spray-painting, sandblasting, deburring, grinding, and shot peening. Specifically, automated path planning for industrial spraying operations offers the potential to automate surface preparation and coating in such environments. Autonomous spray path planners in the literature have been limited to generally continuous and convex surfaces, which is not true of most real parts. There is a need for planners that consistently handle concavities and discontinuities, such as sharp corners, holes, protrusions or other surface abnormalities when building a path. The path planner uses a slicing-based method to generate path trajectories. It identifies and quantifies the importance of concavities and surface abnormalities and whether they should be considered in the path plan by comparing the true part geometry to the convex hull path. If necessary, the path is then adapted by adjusting the movement speed or offset distance at individual points along the path. Which adaptive method is more effective and the trade-offs associated with adapting the path are also considered in the development of the path planner.
Brown, S. (2018). Collaborative Robotic Path Planning for Industrial Spraying Operations on Complex Geometries. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/3019