Human body trajectory generation using point cloud data for robotics massage applications

Abstract

Intelligent robot for improving the quality of human life is desirable. To let robot perform the intelligent functions of massage which can serve for humans, adaptive massage trajectory generator is needed to suit for different body shape with different people. Base on the state of the art human pose recognition techniques, we develop a methodology to build the relationship between camera and human body and generate the specified massage trajectories. Assume we can detect human pose and label each part of human body, we use the RANSAC algorithm to estimate the frontal and sagittal planes and refine it by calculating the minimum moment of inertia of point cloud. The experimental results demonstrate our work which provide a useful method for massage trajectory generation. As an example of service robot application, this method is useful for executing the massage application autonomously.