In this paper we present an approach to extending the capabilities of telemanipulation systems by intelligently augmenting a human operator's motion commands based on quantitative three-dimensional scene perception at the remote telemanipulation site. This framework is the first prototype of the Augmented Shared-Control for Efficient, Natural Telemanipulation (ASCENT) System. ASCENT aims to enable new robotic applications in environments where task complexity precludes autonomous execution or where low-bandwidth and/or high-latency communication channels exist between the nearest human operator and the application site. These constraints can constrain the domain of telemanipulation to simple or static environments, reduce the effectiveness of telemanipulation, and even preclude remote intervention entirely. ASCENT is a semi-autonomous framework that increases the speed and accuracy of a human operator's actions via seamless transitions between one-to-one teleoperation and autonomous interventions. We report the promising results of a pilot study validating ASCENT in a transatlantic telemanipulation experiment between The Johns Hopkins University in Baltimore, MD, USA and the German Aerospace Center (DLR) in Oberpfaffenhofen, Germany. In these experiments, we observed average telemetry delays of 200ms, and average video delays of 2s with peaks of up to 6s for all data. We also observed 75% frame loss for video streams due to bandwidth limits, giving 4fps video.
['Jonathan Bohren', 'Chavdar Papazov', 'Darius Burschka', 'Kai Krieger', 'Sven Parusel', 'Sami Haddadin', 'William L. Shepherdson', 'Gregory D. Hager', 'Louis L. Whitcomb']
A pilot study in vision-based augmented telemanipulation for remote assembly over high-latency networks