To read this content please select one of the options below:

Robot task programming in complex task scenarios based on spatio-temporal constraint calculus

Jinzhong Li (School of Mechanical Engineering, Dalian University of Technology, Dalian, China)
Ming Cong (School of Mechanical Engineering, Dalian University of Technology, Dalian, China)
Dong Liu (School of Mechanical Engineering, Dalian University of Technology, Dalian, China)
Yu Du (School of Mechanical Engineering, Dalian University of Technology, Dalian, China)

Robotic Intelligence and Automation

ISSN: 2754-6969

Article publication date: 31 July 2023

Issue publication date: 21 August 2023

99

Abstract

Purpose

Robots face fundamental challenges in achieving reliable and stable operations for complex home service scenarios. This is one of the crucial topics of robotics methods to imitate human beings’ advanced cognitive characteristics and apply them to solve complex tasks. The purpose of this study is to enable robots to have the ability to understand the scene and task process in complex scenes and to provide a reference method for robot task programming in complex scenes.

Design/methodology/approach

This paper constructs a task modeling method for robots in complex environments based on the characteristics of the perception-motor memory model of human cognition. In the aspect of episodic memory construction, the task execution process is included in the category of qualitative spatio-temporal calculus. The topology interaction of objects in a task scenario is used to define scene attributes. The task process can be regarded as changing scene attributes on a time scale. The qualitative spatio-temporal activity graphs are used to analyze the change process of the object state with time during the robot task execution. The tasks are divided according to the different values of scene attributes at different times during task execution. Based on this, in procedural memory, an object-centered motion model is developed by analyzing the changes in the relationship between objects in the scene episode by analyzing the scene changes before and after the robot performs the actions. Finally, the task execution process of the robot is constructed by alternately reconstructing episodic memory and procedural memory.

Findings

To verify the applicability of the proposed model, a scenario where the robot combines the object (one of the most common tasks in-home service) is set up. The proposed method can obtain the landscape of robot tasks in a complex environment.

Originality/value

The robot can achieve high-level task programming through the alternating interpretation of scenarios and actions. The proposed model differs from traditional methods based on geometric or physical feature information. However, it focuses on the spatial relationship of objects, which is more similar to the cognitive mechanism of human understanding of the environment.

Keywords

Acknowledgements

This research was supported by the National Natural Science Foundation of China (Grant No. 61873045, 62173064). “Take the lead” Science and Technology Research Project of Liaoning Province under (Grant 2021JH1/10400104).

Since acceptance of this article, the following authors have updated their affiliations: Ming Cong and Dong Liu are at the NingBo Institute of Dalian University of Technology, NingBo, China; Yu Du is at the School of Mechanical Engineering, Dalian Jiaotong University, Dalian, China.

Citation

Li, J., Cong, M., Liu, D. and Du, Y. (2023), "Robot task programming in complex task scenarios based on spatio-temporal constraint calculus", Robotic Intelligence and Automation, Vol. 43 No. 4, pp. 476-488. https://doi.org/10.1108/RIA-03-2023-0020

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

Related articles