A Study on Centralised and Decentralised Swarm Robotics Architecture for Part Delivery System

핵심 개념

The author explores the effectiveness of centralised and decentralised swarm robotics architectures for part delivery systems, highlighting the importance of autonomy and collaboration in industrial applications.

초록

The study investigates the use of drones for parts delivery in factories, emphasizing human-robot collaboration. It compares centralised and decentralised approaches, focusing on efficiency and safety. The research delves into path planning, object tracking, and collision avoidance to optimize drone operations. By combining different functionalities like VSLAM and dynamic collision avoidance, a proposed architecture aims to streamline production processes in smart factories. The study highlights the significance of autonomous logistics in enhancing flexibility and productivity in industrial settings.

통계

Drones are designed for military purposes but now used in various aspects of life.
A combined centralised and decentralised architecture is investigated for collaborative drone operation.
Object tracking/following function allows dynamic real-time path-planning.
PyD-NET model enables real-time monocular depth estimation for autonomous navigation.
Pixhawk 4 Mini QAV250 drone is considered ideal for future applications.

인용구

"The rapidly increasing need for faster production speeds necessitates the application of drones for use in factories."
"Swarm robotics can mitigate issues by imitating animal flocks' behavioral patterns."
"The automation necessary for a parts delivery system could be achieved by employing a swarm of parts delivery drones."

핵심 통찰 요약

A Study on Centralised and Decentralised Swarm Robotics Architecture for Part Delivery System

by Angelos Dima... 게시일 arxiv.org 03-13-2024

https://arxiv.org/pdf/2403.07635.pdf

더 깊은 질문

How can the integration of machine vision enhance the efficiency of drone operations beyond part delivery

The integration of machine vision can significantly enhance the efficiency of drone operations beyond part delivery by enabling autonomous decision-making and navigation. Machine vision allows drones to perceive their environment, identify objects, and make real-time adjustments to their flight path. This capability is crucial for tasks such as obstacle avoidance, dynamic path planning, and object tracking. By leveraging machine vision technology, drones can operate more autonomously in complex environments, reducing the need for human intervention and increasing operational efficiency.

What are potential challenges associated with implementing a decentralized approach to swarm robotics in industrial settings

Implementing a decentralized approach to swarm robotics in industrial settings poses several potential challenges. One major challenge is ensuring effective coordination and communication between individual agents within the swarm without a central control system. Decentralized systems may face issues related to synchronization, task allocation, and overall system optimization. Additionally, maintaining consistency in behavior across multiple autonomous agents can be challenging without centralized oversight. Ensuring robustness against failures or malfunctions in individual agents is another critical challenge when adopting a decentralized architecture for swarm robotics.

How might advancements in autonomous logistics impact traditional manufacturing processes

Advancements in autonomous logistics have the potential to revolutionize traditional manufacturing processes by introducing greater flexibility, efficiency, and scalability. Autonomous logistics systems can streamline material handling processes through automated delivery of parts or components within manufacturing facilities. This automation reduces reliance on manual labor for repetitive tasks like transporting sub-assemblies or tools around production lines. By implementing autonomous logistics solutions, manufacturers can optimize workflow efficiency, reduce lead times, minimize errors in material handling operations, and ultimately enhance overall productivity levels within their facilities.