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Laser-based position guidance for efficient task programming for automated construction equipment in unstructured workspace

Laser-guided automated material handling tasks proposed here has the potential to reduce position data acquisition time while improving safety since there is no need for an operator to manually teach or guide a robotic system in its unstructured workspace which is considered most time consuming in programming robotic tasks. The main objective of the proposed research is to develop a new useful method for rapid local area sensing and develop an efficient communication interface between a robot and sensed data for better planning and control of automated equipment operations in unstructured workspace. The UWP SCARA robot and the Large Scale Manipulator (LSM) at the University of Texas-Austin were used for case studies.