Fwd: [InternetTC] [CFP: Deadline Is Approaching (June 1st)] 1st IEEE LCN Special Track on Algorithmic Solutions for Drone- and Robot-based Networks (ASDRoNet) 2024
-------- Weitergeleitete Nachricht -------- Betreff: [InternetTC] [CFP: Deadline Is Approaching (June 1st)] 1st IEEE LCN Special Track on Algorithmic Solutions for Drone- and Robot-based Networks (ASDRoNet) 2024 Datum: Mon, 27 May 2024 10:38:40 +0000 Von: Lorenzo Palazzetti 000002891733877c-dmarc-request@COMSOC-LISTSERV.IEEE.ORG An: itc@COMSOC.ORG
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**CALL FOR PAPERS**
Dear Researchers/Authors,
You are invited to submit your high-quality research findings to the 1st IEEE LCN Special Track on Algorithmic Solutions for Drone- and Robot-based Networks (ASDRoNet) 2024
Date: October 8-10, 2024
Location: Caen, Normandy, France
ASDRoNet co-located with IEEE LCN 2024
Website: https://asdronet2024.github.io/
Submission link: https://edas.info/index.php?c=32354
**SCOPE**
Drones have transformed into versatile tools with applications across agriculture, environmental monitoring, delivery, and surveillance, revolutionizing operations through real-time data collection and efficient task execution in diverse industries. As technology continues to evolve, the integration of robots alongside drones further enhances their capabilities. Robots can collaborate with drones to perform complex tasks and navigate challenging terrains, increasing efficiency and expanding the scope of applications.
However, challenges impede their optimal performance. Limited energy capacity restricts operational time, especially in extended or remote missions. Moreover, the integration of robots introduces additional complexities in coordination, communication, and task distribution between heterogeneous agents. Such challenges can be solved based on a broad spectrum of algorithms, ranging from traditional combinatorial optimization methods to modern machine learning techniques. Algorithms play a pivotal role in enhancing the efficiency and autonomy of drone and robot systems, enabling them to adapt to dynamic environments, optimize resource utilization, and make intelligent decisions in real-time.
For this Special Track, ASDRoNet 2024, we seek submissions of high-quality papers addressing both theoretical and practical aspects of drone and robot research. Topics of interest include, but are not limited to, route planning, task allocation, resource management, scheduling, and network design for integrated drone and robot fleets. Furthermore, submissions are encouraged to delve into algorithmic advancements, computational complexity analyses, and real-world case studies that demonstrate the synergy between drones and robots in various applications.
**TOPICS OF INTEREST**
- Autonomous sensing
- Topology monitoring
- Remote sensing networks
- Communication protocols
- Modeling and analysis
- Precision agriculture
- Crops monitoring in agriculture
- Bugs monitoring in agriculture
- Environmental monitoring
- Autopilot and UAS autonomy
- Path planning and scheduling
- Parcel delivery
- Cellular networks
- Constrained and multi-objective problems
- Sensors localization
- Tracking techniques
- Cooperative control of multiple vehicles
- Cyber-security communications
- Optimal deployment strategies
- Test-beds and experimental results
- Energy-efficient communications
- Machine learning for communications
**IMPORTANT DATES**
Abstract Submission: M̶a̶y̶ ̶2̶5̶,̶ ̶2̶0̶2̶4̶̶ June 1, 2024
Paper Submission: June 1, 2024
Acceptance Notification: July 13, 2024
Camera Ready: TBD
Early Registration: TBD
**SPECIAL ISSUE**
Selected papers will be invited to the special issue Applications-Driven UAV Routing and Scheduling Algorithms for Autonomous Transportation Systems of ACM Journal on Autonomous Transportation Systems.
We look forward to seeing you at the 1st IEEE LCN Special Track on Algorithmic Solutions for Drone- and Robot-based Networks (ASDRoNet) 2024.
Sincerely,
Lorenzo Palazzetti
PhD Student
Computer Science
University of Florence, Italy ---------------------------------------------------------------------------
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participants (1)
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Lars Wolf