The Robotics group at NMBU participates in a number of groundbreaking research projects within precision agriculture and food production.
About the Robotics group
Agricultural robotics
Agricultural robotics is one of the main research areas of the robotics group at NMBU. The agricultural robotics team has developed its own robotic platform, Thorvald. The team also develops tools and agricultural implements that may be used in all stages of operation in the field, from autonomous precision seeding to weeding and harvesting.
Challenges
Food production and agriculture are facing enormous challenges over the next few years with a growing population and a more challenging climate. The world's population is expected to grow rapidly and an estimated 70% increase in food production is required in just a few decades. Climate changes will not only give global warming, but also more intensive rainfall. This is a huge challenge for conventional agricultural machines. Large and heavy machinery will damage wet soil and will also get stuck in muddy fields.
To overcome these challenges, the agricultural robotics team at NMBU develops innovative and intelligent technological solutions for a more efficient and sustainable agriculture.
The agricultural robot Thorvald
Thorvald robots by polytunnel Photo: Håkon Sparre / NMBU The first prototypes of the Thorvald robot were developed by researchers and students in the agricultural robotics lab at NMBU. Thorvald is a low-cost and light-weight agricultural robot. It is battery driven and has four powerful electric motors which makes it capable of performing work in the field. Four-wheel steering makes it extremely mobile. The frame is flexible, which guarantees that all four wheels are in contact with the ground at all times for optimal traction. The robot can operate up to 10 hours without charging or changing its batteries.
Thorvald is used in several of the research projects that the robotics group participates in, and is currently undergoing further development at Saga Robotics, a private company established by researchers at NMBU.
Read more about ThorvaldIntelligent tools for autonomous operation
One of the main challenges of robotic farming is to develop novel tools that can be used on autonomous robots with considerably less power than a tractor. The agricultural robotics team at NMBU has developed and tested several concepts for autonomous operation that require far less energy than conventional systems. These concepts are used in operations such as:
- Seeding: Tools for optimal seed placement
- Plant health: Disease treatment without the use of chemicals
- Weeding: Intelligent and non-chemical weeding
- Monitoring: Data gathering in the field
Contact
Food automation
The Food Automation Team at NMBU is focused on developing robotic systems to improve efficiency and productivity in the food sector.
ABB robot in use for food automation at NMBU. Photo: Alex Mason To-date the Food Automation Team have worked primarily on challenges affecting the meat industry, where automation in primary production has advanced slowly in comparison to other manufacturing sectors. Even worse, many of the advanced automation on the market today is out of reach of the majority of small-medium producers, i.e. it is uneconomical.
The Food Automation Team therefore have a mission to think differently: to invent and develop automation solutions that are robust, scalable and flexible for Norwegian needs!
Focus areas
The food automation team presently focuses on the following research areas:
- Robotics automation, including processing, adapting manual processes to robotised ones, novel processes.
- Novel sensor technology, including for food quality and real-time monitoring, water content and activity, contamination.
- Artificial intelligence, based on 2D and 3D datasets.
- Robot collaboration in food environments.
- Tooling for automation, including adaptation and "intelligent" tools for adaptive requirements.
- Novel gripping and manipulation solutions, including vacuum grippers for damage-free movement of food objects.
Collaboration
The team enjoys to work on research and innovation activities, particularly those with high industry relevance and involvement. We actively seek new partners to for collaboration, so please get in touch if there is a topic into which we can contribute with our knowledge, expertise and facilities.
Contact
Research projects
Coordinator projects:
- EnTechAgri - Enabling Technologies and People for Next-Generation Precision Agriculture (DIKU UTFORSK, 2022-2026)
Partner projects:
- EyeAM – Digital transformation of meat inspection (RCN, 2022-2025. Coordinated by Animalia AS)
- DIGIFOODS - Digital Food Quality (RCN - SFI research centre, 2020-2028. Coordinated by Nofima)
- Robofarmer – Safe and reliable sensing, learning and control of an autonomous multi-arm agri-robot platform (RCN, 2022-2025. Coordinated by SINTEF Digital)
- GentleMAN – Gentle and Advanced Robotic Manipulation of 3D Compliant Objects (RCN, 2019-2023. Coordinated by SINTEF Ocean)
Former coordinator projects
- RoBUTCHER - A Robust, Flexible and Scalable Robotics Platform (EU H2020, 2020-2023)
- SHAPE - Strawberry Harvester for Polytunnels and Open Fields (RCN, 2020-2023)
- Vision-based control with applications to robotic systems (DIKU UTFORSK, 2017 - 2022)
- GrassRobotics - A novel adaptation strategy for forage production under wet growing conditions - robotization and high quality forages (RCN, 2018 -2022)
- MeaTable - Robotised cells to obtain efficient meat production for the Norwegian meat industry (RCN, 2018 - 2022)
Former partner projects
- Erasmus+ AGreen'Smart (EU Erasmus+, 2021-2023. Coordinated by Junia, France)
- FeedCarrier –Autonomous, robust, and flexible feed delivery robot (RCN, 2019-2022. Coordinated by TKS Agri AS)
- vPheno – Reliable and efficient high-throughput phenotyping to accelerate genetic gains in Norwegian plant breeding (RCN, 2017-2022. Coordinated by BIOVIT, NMBU)
- Future Farm - Tomorrow's digital solutions for the farmer (RCN, 2018-2021. Coordinated by TINE SA)
- Robotic Strawberry Harvester - Testing, validation and go-to-market (RCN, 2019 - 2020. Coordinated by Noronn AS)
- Erasmus+ Smart Farming (EU Erasmus+, 2017-2020. Coordinated by ISA Lille, France)
- Agriculture 4.0 - Intelligent autonomous robots for cost efficient fruit and vegetable production (RCN, 2017-2018. Coordinated by Saga Robotics AS)
- Meat 2.0 - New concept: Meat Factory Cell (RCN, 2016-2020. Coordinated by Nortura SA)
- iProcess - Innovative and Flexible Food Processing Technology in Norway (RCN, 2015-2020. Coordinated by SINTEF Ocean)
- Effect of UV-B used against plant diseases on biological control of arthropod pests in greenhouses and plastic tunnels (UV-Bio) (RCN, 2016-2019. Coordinated by Guren gartneri AS)
- UV-B against fungal diseases in plastic tunnels and greenhouses (UV-Bær) (RCN, 2015-2018. Coordinated by Myhrene AS)
PhD theses
- Yuanyue Ge: Machine learning-based perception to identify and localize pickable strawberries for harvester robots. NMBU, 2022
- Marianne Bakken: Explainable and Data-efficient Learning for Visual Guidance of Autonomous Agri-robots. NMBU, 2021.
- Vignesh Raja Ponnambalam: Row Following Based Navigation Systems for Agricultural Robots. NMBU, 2021.
- Tuan Dung Le: Fusion of a minimalistic set of sensors for mapping and localization of autonomous agricultural robotic systems. NMBU, 2020.
- Ya Xiong: Design and Control of Intelligent Robotic Systems for Applications in Life Sciences: Biological Sample Preparation and Strawberry Harvesting. NMBU, 2019.
- Lars Grimstad: Modular, Mobile Robots for Applications in the Agricultural Domain. NMBU, 2018.
- Cong Dung Pham: Modeling and Control of Kinematically Complex Robotic Systems. NMBU, 2015.
Group members
José Carlos Mayoral-Baños
PhD student
Alexander Lillienskiold
PhD student
Abhishesh Pal
PhD student
Marco Fernandes dos Santos Xaud
PhD student
Associated members
Former members
Ya Xiong
Former PhD student and Postdoc
Vignesh Raja Ponnambalam
Former PhD student
Tuan Dung Le
Former PhD student
Marianne Bakken
Former PhD student
Cong Dung Pham
Former PhD student
Robert Braunschweig
Former PhD student
Yuanyue Ge
Former PhD student and researcher
Michaela Pincekova
Former Head Engineer
Mohamed Tarek Ali Sorour
Former Postdoc