论文标题
使用2D轮廓的子空间投影对基于视觉的可变形和刚性对象操纵
Vision-based Manipulation of Deformable and Rigid Objects Using Subspace Projections of 2D Contours
论文作者
论文摘要
本文提出了使用可变形/刚性对象的图像轮廓基于统一的基于视觉的操作框架。该机器人没有使用人为定义的提示，而是自动从处理的视觉数据中学习功能。我们的方法同时生成 - 从相同的数据中生成视觉特征和将它们与机器人控制输入相关联的相互作用矩阵。特征向量和控制命令的提取是在线和自适应进行的，很少有数据以供初始化。该方法允许机器人在不知道刚性还是可变形的情况下操纵对象。为了验证我们的方法，我们使用可变形和刚性对象进行数值模拟和实验。
This paper proposes a unified vision-based manipulation framework using image contours of deformable/rigid objects. Instead of using human-defined cues, the robot automatically learns the features from processed vision data. Our method simultaneously generates -- from the same data -- both, visual features and the interaction matrix that relates them to the robot control inputs. Extraction of the feature vector and control commands is done online and adaptively, with little data for initialization. The method allows the robot to manipulate an object without knowing whether it is rigid or deformable. To validate our approach, we conduct numerical simulations and experiments with both deformable and rigid objects.
