Grip State Recognition for Enabling Safe Human-Robot Object Handover in Physically Collaborative Construction Work

Abstract

Physical interactions between humans and construction robots must inevitably occur under a capacity-based task allocation scheme for successful implementation of a human-robot collaboration (HRC) based workflow. For example, in staging and installing components, a robot can complete physically challenging material handling tasks and a human worker can then creatively manipulate the materials for installation. When materials are handed over from robots to humans, tandem manipulation of objects and physical interaction is necessary. However, this poses several challenges to human workers’ safety, as the objects might fall or break, if the robot incorrectly perceives the human worker’s grip state. This paper considers object handovers between robots and humans and explores how to build a safe tandem HRC framework by letting the robot imitate the mutual physical state adaptation dynamics inherent in human co-workers. To build such a human physical state-aware robot controller, this paper first proposes the use of a haptic glove-based sensing system to capture the grip strength and gesture of construction workers simultaneously. Secondly, the programming by demonstration (PbD) method is used to automatically program a robot through a one-shot demonstration of natural handover processes without requiring the demonstrators (i.e., construction workers) to have computational or programming expertise. The proposed method outperforms prior robot-to-human object handover studies in handling eight construction materials of random shape, dimensions, and weight distribution. In addition, to enable such construction HRC implementations to readily comply with global safety standards, the proposed method is implemented to adhere to ISO 15066:2016 guidelines.