论文标题
桌面场景仅重建无碰撞操纵器控制的桌面场景
RGB-Only Reconstruction of Tabletop Scenes for Collision-Free Manipulator Control
论文作者
论文摘要
我们提出了一个仅使用世界上RGB视图的机器人操纵器的无冲突控制系统。桌面场景的感知输入由RGB摄像机的多个图像（无深度）提供，该图像是手持式或安装在机器人最终效应器上的。类似NERF的过程用于重建场景的3D几何形状，从该过程中，欧几里得完整签名的距离函数（ESDF）被计算出来。然后使用模型预测控制算法来控制操纵器以达到所需的姿势，同时避免ESDF中的障碍物。我们在我们的实验室收集和注释的真实数据集上显示了结果。
We present a system for collision-free control of a robot manipulator that uses only RGB views of the world. Perceptual input of a tabletop scene is provided by multiple images of an RGB camera (without depth) that is either handheld or mounted on the robot end effector. A NeRF-like process is used to reconstruct the 3D geometry of the scene, from which the Euclidean full signed distance function (ESDF) is computed. A model predictive control algorithm is then used to control the manipulator to reach a desired pose while avoiding obstacles in the ESDF. We show results on a real dataset collected and annotated in our lab.
