Using 3-D LiDAR Data for Safe Physical Human-Robot Interaction

TL;DR

This paper demonstrates how 3D LiDAR data can be used for safe physical human-robot interaction by developing a perception pipeline and safety control system tested in a simulated shop-floor environment.

Contribution

It introduces an end-to-end perception and safety control system using 3D LiDAR data, including a fine-tuned object detection network for pHRI scenarios.

Findings

Effective perception pipeline leveraging LiDAR data was developed.

Safety-based control satisfied speed and separation monitoring criteria.

System outperformed previous approaches in safety and perception accuracy.

Abstract

This paper explores the use of 3D lidar in a physical Human-Robot Interaction (pHRI) scenario. To achieve the aforementioned, experiments were conducted to mimic a modern shop-floor environment. Data was collected from a pool of seventeen participants while performing pre-determined tasks in a shared workspace with the robot. To demonstrate an end-to-end case; a perception pipeline was developed that leverages reflectivity, signal, near-infrared, and point-cloud data from a 3-D lidar. This data is then used to perform safety based control whilst satisfying the speed and separation monitoring (SSM) criteria. In order to support the perception pipeline, a state-of-the-art object detection network was leveraged and fine-tuned by transfer learning. An analysis is provided along with results of the perception and the safety based controller. Additionally, this system is compared with the previous work.