We are offering a fully-funded PhD studentship in system science and engineering to be embedded in the RAS-Berry project. This project will develop autonomous fleets of robots for in-field transportation to aid and complement human fruit pickers. In particular, the project will consider strawberry production in polytunnels. A solution for autonomous in-field transportation will significantly decrease strawberry production costs and be the first step towards fully autonomous robotic systems for berry production.
The project will develop a dedicated mobile platform together with software components for fleet management, long-term operation and safe human-robot collaboration in strawberry production facilities.
RAS-Berry is a collaboration between the Norwegian University of Life Sciences (NMBU) and University of Lincoln, and is looking to employ a total of three postdocs and four PhD students. The successful candidates will have access to state-of-the art research farms that will be equipped with production facilities with industrial standard. The project also has access to a wide variety of agricultural robots with advanced sensors and tools. This equipment is already installed on the research farms and will be made available to the project. There is a strong focus on developing solutions that are robust in realistic scenarios, and extensive field testing is therefore required. In order to coordinate the work of everyone involved in the project, several workshops will be held both in Norway and the UK.
The fellowship is closely related to the main activities of the agricultural robotics group at NMBU. The group has developed the Thorvald I and II agricultural robots, which are highly versatile robots specifically designed for the agricultural domain. The robots operate both indoor in tunnels and greenhouses and in outdoor environments. In order to exploit the great potential of robots in agriculture, these robots rely on accurate information on their own position and their surroundings. Precision operations such as harvesting and removal of weeds requires the accuracy of navigation information to be at the cm-level. Reliable estimates of navigation information with high accuracy is difficult with satellite-based systems alone, so one will have to rely on integrated solutions with information from many types of sensors such as e.g.: inertial sensors and laser scanners. In addition, these robots need to be equipped with the sufficient level of autonomy to be able to operate safely and reliably in a complex and dynamic environment. Task allocation and scheduling tasks for one or multiple robots is an important research topic. The robots need to operate in areas where humans and animals have access, and therefore need to do this in a safe way. In addition, the robots need to communicate with humans, for example ask them for help.
For this position, we seek an individual with a good technical background (computer science, engineering, mathematics, physics, etc), who can evidence excellent programming skills (C++ and Python desired, similar will be considered). Of benefit would be experience with at least one of the following (with related experience beneficial): action recognition techniques, sensor fusion methods, human-robot interaction methodologies, and robot control through ROS.
The deadline for applying for this position has closed.