GPS/RTK Localization-based Agri-Robot for Precision Agri-tasks in Crop Fields (RENE_U23CMP)

22 May 2023
Job Information

Organisation/Company

University of East Anglia

Research Field

Computer science » Other

Researcher Profile

First Stage Researcher (R1)

Country

United Kingdom

Application Deadline

19 Jun 2023 – 23:59 (Europe/London)

Type of Contract

Other

Job Status

Other

Offer Starting Date

1 Oct 2023

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Agricultural robots are widely used to tackle labour-intensive, repetitive, and physically demanding tasks. Precise localization and mapping are important to guide the robots to complete the tasks in the field. Global Navigation Satellite System (GNSS) based systems are widely used in agricultural applications for localization purposes. However, these GNSS standalone-based localization systems can only achieve accuracy in the range of 1-10 meters, so the robots usually follow the long corridors in regular crop fields. The walls (e.g., plants) are detected by LiDAR, which is used to calibrate the robot’s location. Moreover, in many agricultural environments, satellite signals are unavailable or inaccurate, or long corridors and regular field scenarios are not available, which leads to the need for advanced solutions independent from these signals.

 

The proposed solution can achieve accuracy in the range of 5-10 cm and has the following work packages (WPs).

 

WP1: Use GPS / RTK for outdoor localization of the robot.

WP2: Use App (camera/drone) to plot the field map and upload it to the Cloud server for processing. Based on the data sent from App, the Cloud server gets back route info to the robot so that the robot can automatically follow the route info in the field. The route info is based on the complete coverage path planning algorithm to cover all the field areas with the shortest path.

WP3: Use cameras and LiDAR to detect and analyse objectives so that the robot can do agri-tasks.

WP4: Raspberry Pi 4 + Jetson Xavier NX  powered vehicle, which can move based on time series location data from WP1 and processing camera and LiDAR data from WP3. Communication modules (e.g., 4G/5G, Wi-Fi) are used to connect a smart device and the Cloud server.

 

Entry requirements & funding notes

This PhD project is in a competition for studentships allocated to the School of Computing Sciences as a direct result is increased PGT student fee income for the MSc Courses in Cyber Security, Data Science and Computing Sciences.  All successful candidates will be expected to support PGT Lab sessions from October 2023 and related activities as allocated in support of these programmes within the working hours permitted for full-time Postgraduate Researchers.

 

Funding comprises ‘home’ tuition fees and an annual stipend (2022/23 rate is £17,668, 2023/24 tbc) for a maximum of 3 years.

Applications are welcomed, and funding is available, to UK applicants only who have the right to work in the UK. 

Requirements

Research Field

Computer science » Other

Education Level

Undergraduate

Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

UEA

Country

United Kingdom

City

Norwich

Postal Code

NR4 7TJ

Street

Earlham Road

Geofield

Where to apply

Website

https://www.uea.ac.uk/apply/postgraduate/research

Contact

City

Norwich

Website

https://www.uea.ac.uk/study/postgraduate/research-degrees/phds-and-studentships

Street

University of East Anglia, Norwich Research Park, Norwich

Postal Code

NR4 7TJ

STATUS: EXPIRED