TAILOR: Teaching with Active and Incremental Learning for Object Registration

TAILOR: Teaching with Active and Incremental Learning for Object Registration
Title:
TAILOR: Teaching with Active and Incremental Learning for Object Registration
Other Titles:
AAAI Demo
Publication Date:
18 May 2021
Citation:
nil
Abstract:
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.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR - AME Programmatic Funding Scheme
Grant Reference no. : A18A2b0046
Description:
Please find the electronic reference to the article in the publication URL provided.
ISBN:
nil
Files uploaded:


File Size Format Action
aaai-demo2020.pdf 5.16 MB PDF Open
aaai-2021.pdf 5.04 MB PDF Open