Towards advanced robotic manipulation for nuclear decommissioning: A pilot study on tele-operation and autonomy

TLDR

The nuclear industry has relied on rudimentary teleoperation with aging 1960s‑style Master‑Slave devices, and robot use has been limited despite high remote handling needs. This study aims to develop advanced robotics for nuclear waste handling, enabling novice operators to quickly learn manipulation tasks and to use autonomous assistance to boost throughput, reduce errors, and improve safety, while applying human‑factors methods for rigorous evaluation. The pilot experiments compare direct teleoperation of a robot arm with human‑supervised semi‑autonomous control that employs computer vision, visual servoing, and autonomous grasping algorithms. Results show novice operators rapidly improve with training, that training demands increase with task complexity, and that autonomous techniques enhance overall task performance.

Abstract

We present early pilot-studies of a new international project, developing advanced robotics to handle nuclear waste. Despite enormous remote handling requirements, there has been remarkably little use of robots by the nuclear industry. The few robots deployed have been directly teleoperated in rudimentary ways, with no advanced control methods or autonomy. Most remote handling is still done by an aging workforce of highly skilled experts, using 1960s style mechanical Master-Slave devices. In contrast, this paper explores how novice human operators can rapidly learn to control modern robots to perform basic manipulation tasks; also how autonomous robotics techniques can be used for operator assistance, to increase throughput rates, decrease errors, and enhance safety. We compare humans directly teleoperating a robot arm, against human-supervised semi-autonomous control exploiting computer vision, visual servoing and autonomous grasping algorithms. We show how novice operators rapidly improve their performance with training; suggest how training needs might scale with task complexity; and demonstrate how advanced autonomous robotics techniques can help human operators improve their overall task performance. An additional contribution of this paper is to show how rigorous experimental and analytical methods from human factors research, can be applied to perform principled scientific evaluations of human test-subjects controlling robots to perform practical manipulative tasks.