Task Automation in Construction Sites: Robot Learning from Teleoperated Demonstrations

Abstract

Easy, reliable and fast learning from demonstration approaches are desirable for task automation in construction sites. Unlike in classic assembly industry where the robot acts in a well-controlled setting, construction sites are unstructured and constantly changing environments. Therefore both workers and robots have to easily adapt to new working scenarios. In this paper we propose a method for automating the joint filling with mastic using a single human demonstration. The demonstration is performed by a human via teleoperation. The learning phase aims at estimating the appropriate tuning parameters of the admittance controller used to reproduce the human motion. Early stage laboratory testings presented in this document demonstrate the validity of the proposed learning scheme.