arrow
Return

Off-Line Programming Framework for Sorting Task Based on Human-Demonstration

delete2025-01-01
delete1
PRE
AI
W
Wei Du
C
Cheng Ding
吴建华 (Jianhua Wu) *
Z
Zhenhua Xiong
DOI:10.1109/TASE.2024.3376712delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Sorting tasks are typical applications in the product and industrial domains. When facing new settings, such as different types of objects and their positions, the system has to be reprogrammed by experienced engineers, which decreases production efficiency and increases labour and downtime costs. In this paper, an off-line programming framework for sorting tasks based on human demonstration has been developed, taking advantage of machine vision and programming-by-demonstration concepts. Only one eye-to-hand depth camera has been used to record both the demonstrated trajectory and the corresponding relationship of the sorting task. A feature generalization algorithm has also been proposed to ensure that the system is able to reproduce the sorting task using both the key features of the trajectory and the sorting features. Finally, tracking, object and target matching, and generalization experiments have been conducted using the JAKA Zu7 robot with different types of fruit models and target boxes. The results show that the proposed framework is able to record the sorting trajectory at a frequency of 10 Hz, acquire and maintain the sorting relationship after new demonstration, and automatically reproduce the sorting task in new settings. Note to Practitioners-This paper is motivated by a goal to accomplish intuitive and user-friendly off-line programming for sorting task. The programming framework should be usable by non-experts and be able to complete programming tasks with a few demonstrations when faced with new scenarios, such as different types of objects, different correspondence relationships of the object, and different positions of the object. By observing the human demonstrated sorting tasks, the above-mentioned features can be effectively extracted, so as to complete the convenient teaching. The underlying principle of this paper is to let the robot observe human demonstrated sorting task by a depth camera, tracking the relative trajectory between the object and box as well as recording their matching information. The key features of the trajectory are extracted and further generalized combing the matching information to automatically reproduce the executable path in different settings. The proposed framework allows the users without prior programming knowledge to program the sorting task in new setting by simply conducting the pick and place process with their hands.
Keywords:
Sorting task
programming by demonstration
object tracking
corresponding relationships
path reproduction

Journal

IEEE Transactions on Automation Science and Engineering cover
IEEE Transactions on Automation Science and Engineering
IF:
6.4
Papers:
5.0K
Citations:
1.6W

Organization

S
shanghai jiao tong university
Scholars:
15.7W
Papers: 11.7W
Citations: 159
Cited Papers

Cited Papers

Recent Advances in Robot Learning from Demonstration
err2020-05-03
err398
errOAAI
errRavichandar, Harish; Polydoros, Athanasios S.; Chernova, Sonia; Billard, Aude
errShare
errSave
Rule-Based Safe Probabilistic Movement Primitive Control via Control Barrier Functions
err2023-07-01
err7
PREAI
errDavoodi, Mohammadreza; Iqbal, Asif; Cloud, Joseph M.; Beksi, William J.; Gans, Nicholas R.
errShare
errSave
Short-lived immunity against pertussis, age-specific routes of transmission, and the utility of a teenage booster vaccine
err2012-01-01
err0
errOAAI
errJennie S. Lavine; Ottar N. Bjørnstad; Birgitte Freiesleben de Blasio; Jann Storsaeter
errShare
errSave
Template-based imitation learning for manipulating symmetric objects*
err2021-10-01
err0
PREAI
errDing, Cheng; Du, Wei; Wu, Jianhua; Xiong, Zhenhua
errShare
errSave
errShare
errSave
ENERGY SAVING ANALYSIS USING ENERGY INTENSITY USAGE AND SPECIFIC ENERGY CONSUMPTION METHODS
err2021-01-01
err0
errOAAI
errJuan Espindola; Farah Nazifa Nourin; Mohammad D. Qandil; Ahmad I. Abdelhadi; Ryoichi Samuel Amano
errShare
errSave
A Novel Illumination-Robust Hand Gesture Recognition System With Event-Based Neuromorphic Vision Sensor
err2021-04-01
err29
errOAAI
errChen, Guang; Xu, Zhongcong; Li, Zhijun; Tang, Huajin; Qu, Sanqing; Ren, Kejia; Knoll, Alois
errShare
errSave
researcher View more