Swarm dePloyment in Autonomous Robot TeleoperAtioNs for Load-Intensive Flight and Transport

This thesis addresses the design and implementation of a single-master multi-slave (SMMS) au- tonomous system, focusing on a fleet of heterogeneous unmanned aerial vehicles (UAVs) tasked with transporting a payload in response to human teleoperation input. Centralized interaction with the external environment is managed by a designated leader UAV, which handles communication with the operator and coordinates each phase of the task, from synchronization to formation control. The fleet employs consensus-based algorithms to converge at the payload’s location and maintain a formation during its transport through the environment. Additionally, a collision-avoidance mechanism based on artificial potential fields ensures safe maneuvering. The flexibility of the developed framework, along with its scalable design, allows for seam- less adaptation to a wide variety of applications, both in terms of task complexity and system configuration.

Publication Details

Journal
Electronic Theses and Dissertations Repository (University of Pisa)
Published
2024-11-28
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
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article

Swarm dePloyment in Autonomous Robot TeleoperAtioNs for Load-Intensive Flight and Transport

Electronic Theses and Dissertations Repository (University of Pisa)
Distributed Control Multi-Agent Systems
article

Swarm dePloyment in Autonomous Robot TeleoperAtioNs for Load-Intensive Flight and Transport

article en

Abstract

This thesis addresses the design and implementation of a single-master multi-slave (SMMS) au- tonomous system, focusing on a fleet of heterogeneous unmanned aerial vehicles (UAVs) tasked with transporting a payload in response to human teleoperation input. Centralized interaction with the external environment is managed by a designated leader UAV, which handles communication with the operator and coordinates each phase of the task, from synchronization to formation control. The fleet employs consensus-based algorithms to converge at the payload’s location and maintain a formation during its transport through the environment. Additionally, a collision-avoidance mechanism based on artificial potential fields ensures safe maneuvering. The flexibility of the developed framework, along with its scalable design, allows for seam- less adaptation to a wide variety of applications, both in terms of task complexity and system configuration.

Electronic Theses and Dissertations Repository (University of Pisa)
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Distributed Control Multi-Agent Systems
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