Advances in automated driving systems (ADSs) have shifted the primary responsibility of
controlling a vehicle from human drivers to automation. Framing driving a highly automated …

This paper presents a comparative study of teleoperation methods of robotic manipulators
aiming at application to the decommissioning operation of the primary containment vessel …

Large-scale data is an essential component of machine learning as demonstrated in recent
advances in natural language processing and computer vision research. However …

This work compared human-robot shared and supervisory control of remote robots for
dexterous manipulation, and examined how the reliability of robot autonomy affects human …

Sequential decision-making (SDM) is a common type of decision-making problem with
sequential and multistage characteristics. Among them, the learning and updating of policy …

Robotics holds the potential to streamline the execution of repetitive and dangerous tasks,
which are difficult or impossible for a human operator. However, in complex scenarios, such …

In the context of teleoperation, arbitration refers to deciding how to blend between human
and autonomous robot commands. We present a reinforcement learning solution that learns …

This paper presents a teleoperation system that includes robot perception and intent
prediction from hand gestures. The perception module identifies the objects present in the …

We propose a formalism for shared control, which is the problem of defining a policy that
blends user control and autonomous control. The challenge posed by the shared autonomy …

In the teleoperation system of a dual-arm manipulator developed to retrieve fuel debris and
reactor interior structures at the Fukushima Daiichi Nuclear Power Plant, we used software …