Utilizing Inpainting for Training Keypoint Detection Algorithms Towards Markerless Visual Servoing
Sreejani Chatterjee,Duc Doan,Berk Calli,Sreejani Chatterjee,Duc Doan,Berk Calli
This paper presents a novel strategy to train keypoint detection models for robotics applications. Our goal is to develop methods that can robustly detect and track natural features on robotic manipulators. Such features can be used for vision-based control and pose estimation purposes, when placing artificial markers (e.g. ArUco) on the robot’s body is not possible or practical in runtime. Prior ...
