TY - JOUR AU - Xu, Qianli AU - Gauthier, Nicolas AU - Liang, Wenyu AU - Fang, Fen AU - Tan, Hui Li AU - Sun, Ying AU - Wu, Yan AU - Li, Liyuan AU - Lim, Joo-Hwee PY - 2021/05/18 Y2 - 2024/03/28 TI - TAILOR: Teaching with Active and Incremental Learning for Object Registration JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 35 IS - 18 SE - AAAI Demonstration Track DO - 10.1609/aaai.v35i18.18031 UR - https://ojs.aaai.org/index.php/AAAI/article/view/18031 SP - 16120-16123 AB - When deploying a robot to a new task, one often has to train it to detect novel objects, which is time-consuming and labor- intensive. We present TAILOR - a method and system for ob- ject registration with active and incremental learning. When instructed by a human teacher to register an object, TAILOR is able to automatically select viewpoints to capture informa- tive images by actively exploring viewpoints, and employs a fast incremental learning algorithm to learn new objects without potential forgetting of previously learned objects. We demonstrate the effectiveness of our method with a KUKA robot to learn novel objects used in a real-world gearbox as- sembly task through natural interactions. ER -