A preliminary study of an intent-recognition-based traded control architecture for high latency telemanipulation

Abstract

Despite the availability of increasingly more robust machine perception and control algorithms, human operators are still needed to directly control robotic systems in extreme environments where there is a high cost of failure. This paper reports a novel architecture for semi-autonomous teleoperation over high-latency telemetry and the results of a 15-subject user study used to evaluate that architecture. The intent-recognition-based traded control (IRTC) architecture recognizes operator intent based on remote scene and task modeling, and automatically trades control to an autonomous reactive subsystem. Each subject participated in one two-hour session during which they controlled a single simulated redundant robotic manipulator with 4000ms of closed-loop latency. Subjects continuously assemble and disassemble a 3D lattice structure with or without IRTC-based assistance. The user study showed that the IRTC system improved operator performance in the simulated multi-object assembly task. All source code for conducting the experiment including the simulation and data processing is available online under a permissive open-source license.