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Tests of the Jellyfishbot completed

As a part of MUDP sponsored project, we have tested the Jellyfishbot in several sites including Karrebæksminde, Køge Marina and Marselisborg Marina. The tests show that the robot performs efficient collection of macroalgae – it is primarily eelgrass that has been collected, which has between 200-400 grams pr. sample.

The design of the robot platform with a net which is pulled behind the robot for the collected biomass seems to be a very efficient design. However, the capacity of the robot is low as the weight of biomass quickly exceeds the capacity of the robot. Already at 300-400 grams of collected biomass, the robot has problems navigating, as the load becomes too heavy and the propulsion is negatively affected. In addition, the robot has difficulty navigating when there are waves. Further work must be done with other types of robot solutions, which have higher capacity and are more robust to Danish weather conditions.

Yet another CO2 measurement and test of the JellyFish robot

The 22nd of September the trip went to Karrebæksminde to validate the Jellyfish robot and do measurements of CO2 in the habour.

Karrebæksminde is an idyllic spot that attracts thousands of tourists in the summertime. It is an old fishing village with a few active fishermen left. 250 metres from the Inner Harbour is one a beach area

Vesterhave beach is a sandy beach about 8-10 m wide and eelgrass is found in heaps on the beach. A digger is used to remove seaweed, evident by the digger itself being parked next to the beach entrance. Only a little odor nuisance. Eelgrass spread all over the beach, with certain areas having larger piles than others. The area is considered to be prone for macro algae flushing.


The port also contain eelgrass but this depends very much on the direction of the wind, and also on the pass by industrial sand extractor ships.

We spend a few hours on collecting eelgrass and measuring CO2 in the habour and at the beach. The collection was approximate 1.2 kg on hour sailing.

BrainBotics are collaborating with SDU on CO2 measurements of algae

You can reduce the amount of emitted greenhouse gases by removing seaweed that decomposes on the beach, as rotten seaweed emits methane and CO2.

The quantity and type of algae varies for each location and can be significantly different from locations that are geographically close to each other. This work package aims to find relevant places to collect aquatic biomass as well as measurements of CO2 emissions from the biomass. Selection of collection sites will be based on quantities of available biomass, access to the site, the type of algae present as well as environmental technical conditions and permits from local authorities. The assessment of this will take place via direct inspection, dialogue with local authorities, overflight with drones and by measurements of how much CO2 emissions the algae make up in water and on the beach, respectively. This preparatory work forms the basis for future consolidated assessment of the potential for reducing greenhouse gases through large-scale removal of macroalgae and eelgrass in the water.

Department of Biology, SDU (BI-SDU) is a subcontractor in the project. The institute focuses on basic and applied research in natural and restored marine ecosystems and focuses specifically on human impacts, including eutrophication and climate change. In BI-SDU, they can provide the evidence-based knowledge and analysis required to test the composition of aquatic biomass and the potential greenhouse gas emissions of methane and CO2, while this material is submerged and degraded. These tasks build on the conclusions from the project Interreg CONTRA, of which BI-SDU is a partner. In BI-SDU, assistant professor (assistant professor) Cintia O. Quintana coordinates the field and laboratory activities, data processing and interpretation. Cintia O. Quintana has more than 12 years of experience in working with Danish marine flora and fauna as well as biogeochemistry and cycles of C, N and P. Thomas Busk, research assistant at SDI-BI and has approx. 3 years of experience, through Interreg CONTRA, with measuring greenhouse gases in the field and providing environmental assessment of beach flushing.

Jellyfishbot now in operation in Denmark

BrainBotics has got their hands on a Jellyfishbot which is a small robot designed to collect floating waste and oil spills. This bot is an efficient and flexible solution to water decontamination of more or less widespread and sheltered areas: ports, marinas, lakes, canals, but also leisure centers, hotel residences and industrial facilities.

Technical Specifications
– Dimensions: L 70 cm, l 70 cm, h 50 cm
– Weight: approx. 20 kg
– Working time: between 4 to 6 hours
– Remote control range: >1 km
– Maximum speed: 2 knots
– Surface: approx. 1000 m²/h (average speed: 1 knot)
– Packaging dim. : 76 x 76 x 60 cm / 35

The 80 L net is made of strong mesh fabric (1 mm mesh). Made to measure, it collects floating waste of small dimensions with 10 to 15 cm deep and has a very long lifespan. The net is attached to a removable frame allowing an easy net recovery: there is no need to take the robot out of the water. The net allows to drain the waste during its recovery.

So far the robot has been test in Skive Fjord, were we have collected samples of sea lettuce.

New project funded by the Danish Ministry of Environment

BrainBotics has just been granted a project by EcoInnovation under the Ministry of the Environment. In this project, we will investigate the commercial value and environmental impact of collecting excess algae (aquatic biomass) with robot technology before the biomass begins to decompose.

Collecting seaweed in the water, before it starts to decompose, will avoid emissions of GHG (CH4) which have a high CO2 equivalent and remove excess nutrient (phosphorous & nitrogen) from the ecosystem up to 10 times more efficiently than when seaweed decays on the coastline. Removal of 10.000 tons fresh seaweed avoids methane emissions by an estimated 5.422 tons CO2e and removes 400 tons nitrogen and five tons phosphorous, and lead to additional CO2 reduction when using algae as a sustainable raw material.

Increasing emissions of fertilizers have led to eutrophication and an increased bloom of algae in lakes, fjords and the world’s oceans. When algae are washed up on the beach and decompose, they emit greenhouse gases including CO2, toxins and cause strong odor nuisances in local areas. In addition, high concentrations of algae damage marine ecosystems and adversely affect the fishing and tourism industries, as well as a number of related industries. To avoid this, manual collection of washed-up algae takes place at beaches and coasts.

Collection today is often based on construction machinery that collects biomass of little or no economic value due to the level of degradation and as the biomass has been mixed with sand and other materials. If the biomass is sufficiently fresh and clean, it can be used as a raw material in several product chains, e.g. as biodegradable packaging, for animal feed and as fertilizer. In less pure form, the biomass can be used as a building material, textile and as a CO2 neutral bioenergy source or biochar. Collecting mass deposits of algae has the positive effect that it provides better conditions for reduced local oxygen depletion as well as increased biodiversity in the local benthic fauna, as one removes nutrients, nitrogen (N) and phosphorus (P), contained in the seaweed biomass from the marine environment.

Simulating robotic biomass collection

Sometimes it is not possible to the real-world evaluation of robotics solutions. This can be due to time, economy or in our case – the weather. In order to mitigate this, a virtual environment representing a test site was programmed in Unity which is a cross-platform game engine developed by Unity Technologies. Simulation is becoming an increasingly important part of robotic application development and validating applications in simulation before deploying to the robot can shorten iteration time by revealing potential issues early. Although the simulated environment in this case is a simplified model of the real world, it can be used to compare the performance of different autonomous navigation methods.

The model of the harbor was based on a drone photo which constituted the model and the underlaying plane of the simulation environment.

The model consisted of the following objects:

  • A 3D model of a WasteShark provided by RanMarine
  • Models of biomass
  • 3D models of boats
  • 3D models of piers surrounding the harbor and boat walks
  • Virtual waypoints for navigation purpose

WasteShark. The WasteShark was modelled using a 3D CAD-model of the WasteShark-platform which was provided by RanMarine. The steering behavior was modelled to resemble the real platform, making is able to move forwards and backwards while rotating around its own axis.

Collection of algae was simulated by using Unity built-in collision detection. When the WasteShark collided with biomass, this counted as a collection of the biomass. This only happened, when the WasteShark was moving forward representing the opening of the platform which is only at one side.

The size of the WasteShark was scaled to represent the corresponding size in the harbor, based on the drone-photo. The speed of the vessel however was arbitrary, as only comparison between different navigation plans (not the absolute values) are of primary interest here.