论文标题
基于仅RGB的物体姿势估计的6D机器人组件
6D Robotic Assembly Based on RGB-only Object Pose Estimation
论文作者
论文摘要
基于视觉的机器人组装是一项至关重要但又具有挑战性的任务，因为与多个对象的相互作用需要高度的精度。在本文中，我们提出了一个集成的6D机器人系统，以感知，掌握，操纵和组装宽度，以紧密的公差。为了提供仅在现成的RGB的解决方案，我们的系统建立在单眼6D对象姿势估计网络基础上，该网络仅使用合成图像训练，该图像利用了基于物理的渲染。随后，提出了姿势引导的6D转换以及无碰撞组装来构建具有任意初始姿势的任何设计结构。我们的新型3轴校准操作通过解开6D姿势估计和机器人组件进一步提高了精度和鲁棒性。定量和定性结果都证明了我们提出的6D机器人组装系统的有效性。
Vision-based robotic assembly is a crucial yet challenging task as the interaction with multiple objects requires high levels of precision. In this paper, we propose an integrated 6D robotic system to perceive, grasp, manipulate and assemble blocks with tight tolerances. Aiming to provide an off-the-shelf RGB-only solution, our system is built upon a monocular 6D object pose estimation network trained solely with synthetic images leveraging physically-based rendering. Subsequently, pose-guided 6D transformation along with collision-free assembly is proposed to construct any designed structure with arbitrary initial poses. Our novel 3-axis calibration operation further enhances the precision and robustness by disentangling 6D pose estimation and robotic assembly. Both quantitative and qualitative results demonstrate the effectiveness of our proposed 6D robotic assembly system.
