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In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
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Toward a Generic Framework for Mission Planning and Execution with a Heterogeneous Multi-Robot System.

Mohsen Denguir1, Ameur Touir2, Achraf Gazdar1

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Summary
This summary is machine-generated.

This study introduces a framework for coordinating ground and aerial robots in complex environments. It enables adaptable mission execution and optimizes collaboration for tasks like exploration and data collection.

Keywords:
UAVUGVdecentralized controlformation controlformation stabilityheterogeneous multi-robot systemsmission planningtask allocation

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Science

Background:

  • Coordinating heterogeneous robots (unmanned ground vehicles and unmanned aerial vehicles) in dynamic environments presents significant challenges.
  • Existing systems often lack scalability and adaptability for complex, unstructured mission scenarios.

Purpose of the Study:

  • To develop a comprehensive framework for mission planning and execution in heterogeneous multi-robot systems.
  • To enhance coordination, task allocation, and resource optimization for unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs).

Main Methods:

  • A decentralized control strategy for adaptive mission execution in 2D and 3D spaces.
  • Implementation of a robust task allocation algorithm and dynamic formation control.
  • Utilizing the ROS 2 communication protocol for reliable inter-robot information exchange.

Main Results:

  • Demonstrated effective coordinated exploration and data collection through a case study.
  • Showcased the framework's ability to manage missions while optimizing robot collaboration.
  • Validated the system's scalability and maintainability due to its loosely coupled architecture.

Conclusions:

  • The proposed framework provides a scalable and adaptable solution for multi-robot coordination in challenging environments.
  • This work advances the field of heterogeneous robotic systems by enabling robust mission planning and execution.
  • The framework facilitates efficient collaboration between UGVs and UAVs for complex tasks.