This paper proposes a unified vision-based manipulation framework using image contours of deformable/rigid objects. Instead of explicitly defining the features by geometries or functions, the robot automatically learns the visual 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, and requires little data for initialization. Our 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.

本文提出了一个基于视觉的统一操纵框架，该框架使用可变形/刚性物体的图像轮廓。机器人没有通过几何形状或功能明确定义特征，而是自动从处理后的视觉数据中学习视觉特征。我们的方法根据相同的数据同时生成视觉特征以及将它们与机器人控制输入相关联的交互矩阵。特征向量和控制命令的提取是在线且自适应地完成的，并且初始化所需的数据很少。我们的方法允许机器人在不知道物体是刚性还是可变形的情况下操纵它。为了验证我们的方法，我们对可变形和刚性物体进行了数值模拟和实验。