Dynamic Plume Tracking by Cooperative Robots

被引:38
作者
Wang, Jun-Wei [1 ,2 ]
Guo, Yi [1 ]
Faha, Muhammad [1 ]
Bingham, Brian [3 ]
机构
[1] Stevens Inst Technol, Dept Elect & Comp Engn, Hoboken, NJ 07030 USA
[2] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
[3] Naval Postgrad Sch, Dept Mech & Aerosp Engn, Monterey, CA 93943 USA
基金
美国国家科学基金会;
关键词
Cooperative control; dynamic pollutant plume; mobile robots; partial differential equation (PDE); set stability; ENVIRONMENTAL LEVEL SETS; ADAPTIVE-CONTROL; BOUNDARY TRACKING; SENSOR NETWORKS; OIL; VEHICLES; SYSTEMS; SURFACE;
D O I
10.1109/TMECH.2019.2892292
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents cooperative control of autonomous mobile robots to monitor and track dynamic pollutant plume propagation in m-dimensional space. The dynamics of the pollutant plume is modeled by an advection-diffusion partial differential equation (PDE), and the plume front is described by a level set with a prespecified threshold value. We solve the problem of cooperative plume tracking using two cooperating robots under formation control, one is assigned as the sensing robot and the other is assigned as the tracking robot, where the sensing robot estimates the gradient and divergence information of the entire field based on its current concentration measurement, and the tracking robot tracks the plume front and patrols on it. Rigorous convergence analysis is provided using the set stability concept. Numerical simulations of pollutant plume tracking in both two- and three-dimensional spaces demonstrate the effectiveness of the proposed control scheme. This paper extends existing literature from static-level curve tracking to dynamic plume front tracking and presents a PDE-observer-based plume front tracking control design. The results are applicable to emerging environmental monitoring tasks by cooperative robots.
引用
收藏
页码:609 / 620
页数:12
相关论文
共 60 条
[21]  
Kahforoshan D, 2008, MATH COMPUT SCI ENG, P180
[22]   Moth-inspired plume tracing via multiple autonomous vehicles under formation control [J].
Kang, Xiaodong ;
Li, Wei .
ADAPTIVE BEHAVIOR, 2012, 20 (02) :131-142
[23]  
Klenke A., 2006, PROBABILITY THEORY
[24]   Development of a Mechatronics-Based Citizen Science Platform for Aquatic Environmental Monitoring [J].
Laut, Jeffrey ;
Henry, Emiliano ;
Nov, Oded ;
Porfiri, Maurizio .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2014, 19 (05) :1541-1551
[25]  
Li S, 2014, IEEE INT CONF ROBOT, P67, DOI 10.1109/ICRA.2014.6906591
[26]   Cooperative Distributed Source Seeking by Multiple Robots: Algorithms and Experiments [J].
Li, Shuai ;
Kong, Ruofan ;
Guo, Yi .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2014, 19 (06) :1810-1820
[27]   Moth-inspired chemical plume tracing on an autonomous underwater vehicle [J].
Li, W ;
Farrell, JA ;
Pang, S ;
Arrieta, RM .
IEEE TRANSACTIONS ON ROBOTICS, 2006, 22 (02) :292-307
[28]   Building gas concentration gridmaps with a mobile robot [J].
Lilienthal, A ;
Duckett, T .
ROBOTICS AND AUTONOMOUS SYSTEMS, 2004, 48 (01) :3-16
[29]   ROBUSTNESS OF ADAPTIVE CONTROL UNDER TIME DELAYS FOR THREE-DIMENSIONAL CURVE TRACKING [J].
Malisoff, Michael ;
Zhang, Fumin .
SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2015, 53 (04) :2203-2236
[30]   Adaptive control for planar curve tracking under controller uncertainty [J].
Malisoff, Michael ;
Zhang, Fumin .
AUTOMATICA, 2013, 49 (05) :1411-1418