Cooperative Multiple Drone System for Unknown Environment Exploration

Degree type


Closing date

18 July 2022



Citizenship requirement


About the research project

Unmanned Aerial Drones have received attention and have been widely applied in many application domains, including traffic monitoring, and the logistics and environment monitoring. Single drone systems are suffering from short battery life and small working radius, which greatly limit their applications in applications like search and rescue (SAR) or hidden area exploration. Cooperative MDSs is a cutting-edge area in robotics and multi-agent systems (MAS) and can cover many critical limitations in single drone systems. However, the coordination and control of MDSs are still challenging research issues blocking them from many real-world applications.

This project will investigate the use of Reinforcement Learning (RL) in MDS controlling and scheduling. Novel coordination mechanisms will be designed and implemented to support multiple drones to execute exploration tasks in unknown areas. Different with existing drone systems, multiple drones will work together to achieve a common goal in a dynamic environment. Responsibilities and resources will be allocated to different drones in a cooperative manner with learning-based automated coordination’s.

Primary Supervisor

Meet Dr Ananda Maiti


Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:

  • a living allowance stipend of $28,854 per annum (2022 rate, indexed annually) for 3.5 years
  • a relocation allowance of up to $2,000
  • a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)

If successful, international applicants will receive a University of Tasmania Fees Offset for up to four years.

As part of the application process you may indicate if you do not wish to be considered for scholarship funding.


Applicants should review the Higher Degree by Research minimum entry requirements.

Selection Criteria

The project is competitively assessed and awarded.  Selection is based on academic merit and suitability to the project as determined by the College.

Additional essential selection criteria specific to this project:

  • Demonstrated strong research and analytical skills
  • Familiarity with AI techniques and tools

Additional desirable selection criteria specific to this project:

  • Specific skills in reinforcement learning, intelligent agents and robotics

Application process

There is a three-step application process:

  1. Select your project, and check you meet the eligibility and selection criteria;
  2. Contact the Primary Supervisor, Dr Ananda Maiti to discuss your suitability and the project's requirements; and
  3. Submit an application by the closing date listed above.
    • Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
    • As part of your application, you will be required to submit a covering letter, a CV including 2 x referees and your project research proposal.

Following the application closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.

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