Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
2024-02-24
2024-01-04
2023-11-02
Abstract—To be able to navigate in socially complaint fashion and safely, people detection is a very important ability for robots deployed in our social environments. However, it is a challenging task since humans exhibit various poses in daily life as they bend, sit down, touch or interact with each other. A robust people detector should detect humans also in these arbitrary poses. In addition, mobile robots should be able to carry out detection in a real-time manner because our environment is highly dynamic. In this study we developed a fast head and people detector which can, pose invariantly, detect people. Method depends only on depth information of point clouds taken from RGB-D sensors. As a result, it is robust against sudden light and contrast changes. The algorithm runs relying only on CPU, which makes it applicable to mobile robots with low computational resources.