Distributed Multirobot Multitarget Tracking Using Heterogeneous Limited-Range Sensors

Utilizing heterogeneous mobile sensors to actively gather information improves adaptability and reliability in extended environments. This article presents a cooperative multirobot multitarget search and tracking framework aimed at enhancing the efficiency of the heterogeneous sensor network, and co...

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Veröffentlicht in:IEEE transactions on robotics Jg. 41; S. 1755 - 1772
Hauptverfasser: Chen, Jun, Abugurain, Mohammed, Dames, Philip, Park, Shinkyu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: IEEE 2025
Schlagworte:
Aerospace electronics
Capacitive sensors
Distributed robot systems
multirobot systems
networked robots
Partitioning algorithms
Planning
reactive and sensor-based planning
Robot sensing systems
Robots
Sensors
State estimation
Target tracking
ISSN:1552-3098, 1941-0468
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Zusammenfassung:Utilizing heterogeneous mobile sensors to actively gather information improves adaptability and reliability in extended environments. This article presents a cooperative multirobot multitarget search and tracking framework aimed at enhancing the efficiency of the heterogeneous sensor network, and consequently, improving the overall target tracking accuracy. The concept of normalized unused sensing capacity is introduced to quantify the information a sensor is currently gathering relative to its theoretical maximum. This measurement can be computed using entirely local information and is applicable to various sensor models, distinguishing it from previous literature on the subject. It is then utilized to develop a heuristics distributed coverage control strategy for a heterogeneous sensor network, adaptively balancing the workload based on each sensor's current unused capacity. The algorithm is validated through a series of robot operating system (ROS) and MATLAB simulations, demonstrating superior results compared to standard approaches that do not account for heterogeneity or current usage rates.
ISSN:1552-3098
1941-0468
DOI:10.1109/TRO.2025.3543303