Distributed Theory in Applications of Autonomous Vehicles

Deadline for manuscript submissions: 15 January 2024.

Topic Editor (1)

Zongyu  Zuo
Prof. Zongyu Zuo 
Website
Topic Editor
The Seventh Research Division, Beihang University, Beijing 100191, China
Interests: Control of UAVs; Cooperative Control of Multiagent Systems; Nonlinear Control Theory and Applications; Finite-/Fixed-time Stability/Stabilization

Co-Topic Editors (2)

Zhongguo  Li
Dr. Zhongguo Li 
Website
Co-Topic Editor
Department of Computer Science, University College London, London, UK
Interests: Distributed Control; Robotic Path Planning; Multi-Agent Systems; Distributed Learning; Autonomous Systems
Yao  Zou
Prof. Yao Zou 
Website
Co-Topic Editor
University of Intelligence Science and Technology, Beijing 100084, China
Interests: Multi-agent Systems; Distributed Control; Aircraft Control

Topic Collection Information

In recent years, multi-vehicle systems have been extensively investigated and applied.  Distributed theory plays a principal role in coordinating large-scale multi-vehicle systems, which has been featured in cooperative sensing, control, planning, guidance, and other swarm mechanisms. How to coordinate numerous autonomous vehicles to exhibit certain complicated swarm behaviors depends on exquisite distributed theory in sensing, control, planning, and guidance. Besides, distributed techniques require information interaction of neighboring vehicle via network communications. This means that outstanding swarm behaviors depend on perfect interactive protocols. Moreover, a majority of autonomous vehicles, such as UAVs, USVs, and UGVs, are characterized by nonlinear, non-holonomic, and under-actuated attributes. This imposes additional difficulty in their coordination subject to the complexity of internal models. Moreover, autonomous vehicles frequently operate in strange unstructured circumstances. Confronted with environmental disturbances, it becomes difficult to maintain benign cooperative performance. This motivates the introduction of feasible anti-disturbance mechanisms into distributed techniques. 

In this Topic Collection, we invite you to contribute original research articles, brief reports, systematic reviews, systemic and shorter perspectives, opinions, and expert perspectives on all aspects related to the theme of “distributed theory and applications to autonomous vehicles”. Relevant topics include but are not limited to:
  • Distributed control of autonomous vehicles
  • Distributed path/trajectory planning of autonomous vehicles
  • Distributed guidance of autonomous vehicles
  • Formation control of UAVs/UGVs/USVs
  • Methodologies for distributed theory 
  • Distributed sensing
  • Resilient distributed control
  • Robust/Adaptive distributed control 
  • Distributed filter
  • Distributed optimization
  • Collective intelligence
  • Self-organization
  • Multi-vehicle systems
  • Multi-vehicle applications


 

Published Papers (1 papers)

Review

08 November 2023

Review on Drone-Assisted Air-Quality Monitoring Systems

Drone-aided systems have gained popularity in the last few decades due to their stability in various commercial sectors and military applications. The conventional ambient air quality monitoring stations (AAQMS) are immovable and big. This drawback has been significantly overcome by drone-aided low-cost sensor (LCS) modules. As a result, much research work, media information, and technical notes have been released on drone-aided air quality and ecological monitoring and mapping applications. This work is a sincere effort to provide a comprehensive and structured review of commercial drone applications for air quality and environmental monitoring. The collected scientific and non-scientific information was divided according to the different drone models, sensor types, and payload weights. The payload component is very critical in stablility of the multirotor drones. Most study projects installed inexpensive sensors on drones according to the avilibility of the space on drone frame. After reviewing of multiple environmental applications the common payload range was 0 gm to 4000 gm. The crucial elements are addressed, including their relation to meteorological factors, air isokinetics, propeller-induced downwash, sensor mounting location, ramifications etc. As a result, technical recommendations for AQ monitoring assisted by drones are addressed in the debate part. This work will help researchers and environmentalists choose sensor-specific payloads for drones and mounting locations. Also, it enables advanced methods of monitoring parameters that help policymakers to frame advanced protocols and sensor databases for the environment and ecology.

Piyush AshokKokate*
Anirban SMiddey
Shashikant  SSadistap
Gaurav SSarode
Anvesha narayan
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