Abstract
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.
Abstract (translated)
在这项研究中，我们引入了“SARDiM”，一种模块化半自主平台，通过增强混合现实技术，用于工业拆卸任务。通过一个关注电动汽车电池拆卸的案例研究，SARDiM 整合了混合现实、目标分割、遥控、力反馈和可变自主。利用ROS、Unity和MATLAB平台，结合联合阻尼控制器，SARDiM 促进了遥控拆卸。该方法结合了 FastSAM 进行实时物体分割，生成数据，并通过聚类分析算法对其进行处理，以确定组件的质心和高低优先级，将它们按大小和拆卸优先级进行分类。这些数据指导了 Franka Robot 手臂在轨迹规划中的移动。SARDiM 提供了在两种遥控模式之间切换的能力：手动和具有可变自主权的半自主模式。每种模式都通过四种不同的接口方法（IM）进行了评估：直接观察、监视反馈、混合现实与监视反馈、点云混合现实。在八种不同接口方法的评估中，使用 Mode 2。此外，Mode 2-IM4 比 Mode 1-IM1 实现了 2.33% 的时间减少，大大提高了安全性，使其成为在安全距离内操作的理想选择，具有与直接观察环境遥控相同的易用性。
URL
https://arxiv.org/abs/2405.03530
