Autonomous motion planning and task execution in geometrically adaptive robotized construction work

Abstract This research explores a means by which a construction robot can leverage its sensors and a Building Information Model (BIM) to perceive and model the actual geometry of its workpieces, adapt its work plan, and execute work in a construction environment. The adaptive framework uses the Generalized Resolution Correlative Scan Matching (GRCSM) search algorithm for model registration, a new formulation for fill plan adaptation, and new hardware for robotic material dispensing. Joint filling is used as a case study to demonstrate the formulation of an adaptive plan and evaluate a robot's ability to perform adaptive work in an environment where the actual location and geometry of its workpieces may deviate from their designed counterparts. Averaged across five experiments, the robot was found capable of identifying the true position and orientation of the joint's center with a mean norm positioning error of 0.11 mm and orientation error of 1.1 ° . The adaptive framework offers significant promise for a range of construction activities, including those involving objects of complex geometry and detailed work.