Analyzing and improving multi-robot missions by using process mining

被引:0
|
作者
Juan Jesús Roldán
Miguel A. Olivares-Méndez
Jaime del Cerro
Antonio Barrientos
机构
[1] Centre for Automation and Robotics (CAR,Interdisciplinary Centre for Security
[2] UPM-CSIC),undefined
[3] Reliability and Trust (SnT,undefined
[4] uni.lu),undefined
来源
Autonomous Robots | 2018年 / 42卷
关键词
Robotics; Multi-robot; Mission; Process mining; Modeling; Analysis;
D O I
暂无
中图分类号
学科分类号
摘要
Multi-robot missions can be compared to industrial processes or public services in terms of complexity, agents and interactions. Process mining is an emerging discipline that involves process modeling, analysis and improvement through the information collected by event logs. Currently, this discipline is successfully used to analyze several types of processes, but is hardly applied in the context of robotics. This work proposes a systematic protocol for the application of process mining to analyze and improve multi-robot missions. As an example, this protocol is applied to a scenario of fire surveillance and extinguishing with a fleet of UAVs. The results show the potential of process mining in the analysis of multi-robot missions and the detection of problems such as bottlenecks and inefficiencies. This work opens the way to an extensive use of these techniques in multi-robot missions, allowing the development of future systems for optimizing missions, allocating tasks to robots, detecting anomalies or supporting operator decisions.
引用
收藏
页码:1187 / 1205
页数:18
相关论文
共 50 条
  • [41] Multi-robot team coordination using desirabilities
    Saffiotti, A
    Zumel, NB
    Ruspini, EH
    [J]. INTELLIGENT AUTONOMOUS SYSTEMS 6, 2000, : 107 - 114
  • [42] Multi-robot localization using relative observations
    Martinelli, A
    Pont, F
    Siegwart, R
    [J]. 2005 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), VOLS 1-4, 2005, : 2797 - 2802
  • [43] A Memetic Algorithm for the Task Allocation Problem on Multi-robot Multi-point Dynamic Aggregation Missions
    Gao, Guanqiang
    Mei, Yi
    Xin, Bin
    Jia, Ya-Hui
    Browne, Will
    [J]. 2020 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2020,
  • [44] Automated text mining comparison of Japanese and USA multi-robot research
    Watts, RJ
    Porter, A
    Minsk, B
    [J]. DATA MINING V: DATA MINING, TEXT MINING AND THEIR BUSINESS APPLICATIONS, 2004, 10 : 61 - 74
  • [45] Multi-robot coordination
    Kowalczyk, W
    [J]. ROMOCO'01: PROCEEDINGS OF THE SECOND INTERNATIONAL WORKSHOP ON ROBOT MOTION AND CONTROL, 2001, : 219 - 223
  • [47] Improving Multi-Robot Behavior Using Learning-Based Receding Horizon Task Allocation
    Schillinger, Philipp
    Buerger, Mathias
    Dimarogonas, Dimos, V
    [J]. ROBOTICS: SCIENCE AND SYSTEMS XIV, 2018,
  • [48] Map-merging using maximal empty rectangles in a multi-robot SLAM process
    Shahram Hadian Jazi
    [J]. Journal of Mechanical Science and Technology, 2020, 34 : 2573 - 2583
  • [49] Analyzing Multi-agent Activity Logs Using Process Mining Techniques
    Rozinat, A.
    Zickler, S.
    Veloso, M.
    van der Aalst, W. M. P.
    McMillen, C.
    [J]. DISTRIBUTED AUTONOMOUS ROBOTIC SYSTEMS 8, 2009, : 251 - +
  • [50] Multi-Robot Caravanning
    Denny, Jory
    Giese, Andrew
    Mahadevan, Aditya
    Marfaing, Arnaud
    Glockenmeier, Rachel
    Revia, Colton
    Rodriguez, Samuel
    Amato, Nancy M.
    [J]. 2013 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2013, : 5722 - 5729