  In this study, we introduce "SARDiM," a modular semi-autonomous platform
enhanced with mixed reality for industrial disassembly tasks. Through a case
study focused on EV battery disassembly, SARDiM integrates Mixed Reality,
object segmentation, teleoperation, force feedback, and variable autonomy.
Utilising the ROS, Unity, and MATLAB platforms, alongside a joint impedance
controller, SARDiM facilitates teleoperated disassembly. The approach combines
FastSAM for real-time object segmentation, generating data which is
subsequently processed through a cluster analysis algorithm to determine the
centroid and orientation of the components, categorizing them by size and
disassembly priority. This data guides the MoveIt platform in trajectory
planning for the Franka Robot arm. SARDiM provides the capability to switch
between two teleoperation modes: manual and semi-autonomous with variable
autonomy. Each was evaluated using four different Interface Methods (IM):
direct view, monitor feed, mixed reality with monitor feed, and point cloud
mixed reality. Evaluations across the eight IMs demonstrated a 40.61% decrease
in joint limit violations using Mode 2. Moreover, Mode 2-IM4 outperformed Mode
1-IM1 by achieving a 2.33%-time reduction while considerably increasing safety,
making it optimal for operating in hazardous environments at a safe distance,
with the same ease of use as teleoperation with a direct view of the
environment.
