A Mobile Robot Hand-Arm Teleoperation System by Vision and IMU

Abstract

In this paper, we present a multimodal mobile teleoperation system that consists of a novel vision-based hand pose regression network (Transteleop) and an IMU-based arm tracking method. Transteleop observes the human hand through a low-cost depth camera and generates not only joint angles but also depth images of paired robot hand poses through an imageto-image translation process. A keypoint-based reconstruction loss explores the resemblance in appearance and anatomy between human and robotic hands and enriches the local features of reconstructed images. A wearable camera holder enables simultaneous hand-arm control and facilitates the mobility of the whole teleoperation system. Network evaluation results on a test dataset and a variety of complex manipulation tasks that go beyond simple pick-and-place operations show the efficiency and stability of our multimodal teleoperation system.

O2S: Open-source open shuttle

“…The data collected by the IMU sensor is sent via a wireless connection to the robot, which uses it to calculate the movement commands for the motors. We leveraged the framework proposed in [9] and [21] to achieve the gesture-based control strategy.…”