Journal

A removal plan is more useful when an operator can inspect how it was produced, not just read its final list. This work extends language-guided EV battery disassembly with a stronger generator–verifier workflow and an interface exposing intermediate outputs, helping people locate and correct mistakes in the planning process.

Intent prediction becomes useful when it identifies a plausible target early enough to support a person. This study evaluates the manipulation phase of GUIDER on recorded real-robot data, extending the earlier simulation work without claiming an end-to-end deployment of the complete mobile-navigation framework.

Introducing robotics into the nuclear back-end involves more than demonstrating that a machine can complete a task. These proceedings connect my 2025 workshop participation with two contributions on autonomous technologies and safety considerations, bringing technical capability into discussion with human factors, implementation and the evidence needed for responsible deployment.

A short instruction such as “remove the left battery module” hides several decisions: which module is meant, which fasteners block it, what must happen first, and which robot can perform each action. This paper tackles the intent-to-plan part of that problem, turning a perceived scene and a human request into an inspectable removal sequence.

GUIDER—Global User Intent Dual-phase Estimation for Robots—tries to recognise what a teleoperator is working towards without requiring a predefined list of goals. It separates the journey to a work area from the subsequent manipulation, using scene information and human motion to maintain a changing belief about the intended target.

Remote battery disassembly requires both an understanding of the workcell and fine control of physical interaction. This paper combines extended-reality visualisation, haptic feedback and learned motion guidance in a variable-autonomy framework, investigating how the robot can assist an operator without reducing the task to either fully manual or fully autonomous control.