Real-time Object Detection with Deep Learning for Robot Vision on Mixed Reality Device
PubDate: April 2021
Teams: The University of Electro-Communications
Writers: Jiazhen Guo; Peng Chen; Yinlai Jiang; Hiroshi Yokoi; Shunta Togo
Mixed reality device sensing capabilities are valuable for robots, for example, the inertial measurement unit (IMU) sensor and time-of-flight (TOF) depth sensor can support the robot in navigating its environment. This paper demonstrates a deep learning (YOLO model) background, realtime object detection system implemented on mixed reality device. The goal of the system is to create a real-time communication system between HoloLens and Ubuntu systems to enable real-time object detection using the YOLO model. The experimental results show that the proposed method has a fast speed to achieve real-time object detection using HoloLens. This enables Microsoft HoloLens as a device for robot vision. To enhance human-robot interaction, we will apply it to a wearable robot arm system to automatically grasp objects in the future.