Towards a behavior tree-based robotic software architecture with adjoint observation schemes for robotic software development

被引:0
|
作者
Shuo Yang
Xinjun Mao
Yao Lu
Yong Xu
机构
[1] National University of Defense Technology,Key Laboratory of Software Engineering for Complex Systems, College of Computer
来源
关键词
Adjoint sensing and acting; Adjoint observation scheme; Behavior tree; Robotic software architecture;
D O I
暂无
中图分类号
学科分类号
摘要
Nowadays, autonomous robots are increasingly accomplishing tasks in the dynamic world where environment states may change unexpectedly and be partially observable. The robot tasks in dynamic environments generally expect the robot to continuously deliberate upon the task goal while effectively obtaining environmental information with sensor and actuator actions. Implementing the underlying robotic software for such tasks can be rather difficult and tedious. The software developers need to synthetically implement the decision-making issues of controlling and planning, as well as the interactions between robotic sensing and actuating components, which is much more challenging than general-purpose software development. The existing software engineering practices focus on the general-purpose software development issues of modularity and communication, without specialized architectural solutions for the implementation of robotic controlling and decision-making processes, which still limits the implementation efficiency of robotic software in dynamic environments. This paper proposes a general-purpose scheme of adjoint observation between robotic sensing and actuating components, which specifies the integral control loop of controlling, planning, and data flows. The adjoint observation scheme solves the problem of effectively exploring the environment for effective observations by the integral control loop. Then we utilize the Behavior Tree component software architecture for concrete implementation of adjoint observation schemes. More specifically, we propose the Parallel and Fallback tree structure for concrete implementation of adjoint control flows. We also extend the BT architecture with an online planning component and mutual data store mechanism, enabling continuous planning and efficient data communication between robotic sensing and actuating processes. In the experiment, we select the Classical BT approach and Pure ROS-based approach as baseline approaches, to validate the task effectiveness of the adjoint observation scheme and development efficiency of the supporting software architecture.
引用
收藏
相关论文
共 50 条
  • [31] A modern DevOps and serverless architecture for the New Robotic Telescope software infrastructure
    Bento, Joao
    Heffernan, David
    Quintana Rivero, Cesar
    Prieto Antunez, Alberto
    Garner, Adam
    Copley, David
    Fernandez-Valdivia, J. J.
    Leon Gil, Javier
    Barrera Martin, Josue
    Torres, Miguel
    SOFTWARE AND CYBERINFRASTRUCTURE FOR ASTRONOMY VIII, 2024, 13101
  • [32] Autonomous Robotic Platform for Precision Orchard Management: Architecture and Software Perspective
    Mengoli, Dario
    Tazzari, Roberto
    Marconi, Lorenzo
    PROCEEDINGS OF 2020 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR AGRICULTURE AND FORESTRY (METROAGRIFOR), 2020, : 303 - 308
  • [33] A tree-based classification model for analysis of a military software system
    Khoshgoftaar, TM
    Allen, EB
    Bullard, LA
    Halstead, R
    Trio, GP
    IEEE HIGH-ASSURANCE SYSTEMS ENGINEERING WORKSHOP, PROCEEDINGS, 1997, : 244 - 251
  • [34] Tree-based software quality classification using genetic programming
    Liu, Y
    Khoshgoftaar, T
    NINTH ISSAT INTERNATIONAL CONFERENCE ON RELIABILITY AND QUALITY IN DESIGN, 2003 PROCEEDINGS, 2003, : 183 - 188
  • [35] Tree-based software quality estimation models for fault prediction
    Khoshgoftaar, TM
    Seliya, N
    EIGHTH IEEE SYMPOSIUM ON SOFTWARE METRICS, PROCEEDINGS, 2002, : 203 - 214
  • [36] Tree-based Model Predictive Control Strategy for Software Rejuvenation
    Arauz, T.
    Maestre, J. M.
    Quevedo, D.
    Camacho, E. F.
    2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC), 2022, : 1124 - 1129
  • [37] Towards Migrating Resource-Consuming Robotic Software Packages to Cloud
    Wen, Shangmin
    Ding, Bo
    Wang, Huaimin
    Hu, Ben
    Liu, Hui
    Shi, Peichang
    2016 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (IEEE RCAR), 2016, : 283 - 288
  • [38] Modular ROS-based software architecture for reconfigurable, Industry 4.0 compatible robotic workcells
    Simonic, Mihael
    Pahic, Rok
    Gaspar, Timotej
    Abdolshah, Saeed
    Haddadin, Sami
    Catalano, Manuel G.
    Worgotter, Florentin
    Ude, Ales
    2021 20TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS (ICAR), 2021, : 44 - 51
  • [39] A Build System for Software Development in Robotic Academic Collaborative Environments
    Domenichelli, Daniele E.
    Traversaro, Silvio
    Muratore, Luca
    Rocchi, Alessio
    Nori, Francesco
    Natale, Lorenzo
    INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING, 2019, 13 (02) : 185 - 205
  • [40] A Build System for Software Development in Robotic Academic Collaborative Environments
    Domenichelli, Daniele E.
    Traversaro, Silvio
    Muratore, Luca
    Rocchi, Alessio
    Nori, Francesco
    Natale, Lorenzo
    2018 SECOND IEEE INTERNATIONAL CONFERENCE ON ROBOTIC COMPUTING (IRC), 2018, : 33 - 40