We are very excited to announce the official Kick-Off of the AMBULANT Project (Science and Technology Cooperation – Sino-Malta Fund)
The consortium brings together Malta College for Arts Science and Technology – MCAST (Maltese Leader) and AquaBioTech Group in Malta, together with the Chinese partners: China Agricultural University (Chinese Leader), Shandong Laizhou Mingbo Aquatic Products Co. (China), Beijing University of Information Science and Technology (China), Beijing Quanlu Communication and Signal Research and Design Institute Group Co. (China). The official meeting was held online, and we are looking forward to a fruitful collaboration.
What is AMBULANT ?
AutonoMous Bio-mimetic Underwater vehicLe for digitAl cage moNiToring (AMBULANT)
AMBULANT has an intention to create a biomimetic robot with an intelligent monitoring system for identifying seabed habitats, as well as fish and their biomass in aquaculture. This would be a transformation and upgrade of traditional aquaculture, as the technologies used until now put distress on the living organisms because of their frightening appearance, loud noise and poor concealment. Biomimetic, in this case, means it will physically appear and move as a fish.
These robots have high efficiency, high practicality and low disturbance towards fish stocks. They will support environmental protection of commercially important species and detect endangered and invasive species. In aquaculture it will improve fish welfare and monitoring of risk factors, reduce inefficacy in the farming process, as well as further develop monitoring technology, which will lead to economic growth.
This project is funded under the Grant Agreement Number SINO-MALTA-2021-18
What about the goals ?
AMBULANT aims to develop a dynamic monitoring system of deep-water cages through the implementation of a submersible biomimetic robot carrier which will be achieved via the following project objectives:
- Design and construct innovative integrated rigid-flexible coupling hybrid-drive bionic underwater robotic system prototypes with the capability of autonomous 3D positioning and localization within deepwater environments, and reduced noise and disturbance during unmanned underwater monitoring.
- Design and construct a spatiotemporal prediction model for water quality in marine environments and aquaculture.
- Develop and construct a Biomass Estimation Model for fish biomass estimates based on multi-module convolutional networks.
- Develop and construct an automated benthic detection and identification system of key marine features (endangered species, invasive species, benthos type, lost or damaged maritime infrastructure) through machine learning, machine vision prototypes and artificial neural networks.
- Demonstrate the integrated platform for digital deep water net cage comprehensive monitoring system in China. This demonstration will showcase the application of the water quality prediction model and the biomass estimation model.
- Demonstrate in Malta the benthic habitat model for live identification of Maltese marine benthic habitats from ROV captured video in the depth range 10-100 meters.
Our Role in the AMBULANT Project
- Collecting videos of the seabed at different depths around Maltese waters using an ROV equipped with a camera, lighting and GPS
- Converting videos into still images representing a variety of marine habitats
- Exporting the final dataset in an industry-standard format to be used by the AI of the biomimetic robot
- Assessing the model’s performance during the evaluation process from a marine point of view