Laser Point Detection Based on Improved Target Matching Method for Application in Home Environment Human-Robot Interaction

As the population aging becomes more severe, the development of Wheelchair Mounted Robotic Arms (WMRA) has gained greater attention. There are remaining issues that haven't been properly tackled, such as human-robot interaction and real-time performance. In this paper, laser pointer is used to facilitate the interaction between human and the WMRA, and an improved target matching method is proposed for laser point detection in home environment. Firstly, the laser point's characteristics are amplified through the use of channel separation technique and reflective materials. Then, the laser point is separated from the image using background difference method. Finally, through ASUS Xtion, the distance between laser point and the centroid coordination of object is calculated, and then Kinova Jaco robotic arm is used for grasping. The experimental result shows that the algorithm can effectively detect laser point in the home environment, and as a human-robot interaction, the robotic arm successfully completes the task of demo grasp.