Float-E

What it does

A semi-autonomous robot that alleviates oil spill problems, through the use of computer vision to locate and collect these spills; use of a pump to collect and store; and coconut husk as a more cost-effective oil filtration solution from excess water.

Your inspiration

The potential risk for large-scale oil spills to occur can lead to devastating results, causing both environmental and economic damages that can take several years to clean up and recover from. With the existence of offshore rigs as well as the constant transport of oil around the world each year, more autonomous, efficient ways of handling these impacts are being explored. Various researchers have been studying the use of automation to help reduce manual clean-up and further reduce hazardous consequences. Given the risk of these oil spills, we, as researchers, are determined to create and develop an efficient way to minimize health threats.

How it works

Float-E utilizes a user interface that provides options for the user to operate the robot either manually or automatically. If the user chose the manual option, they have the ability to control the robot (moving forward, slowing it down, turning left or right); on the other hand, the system does the maneuvering for the user if it were to be operated with the automatic option. The oil collection mechanism of the robot is dependable on the oil detection/isolation system of the user interface, wherein the user is provided with sliders to adjust the HSV (hue, saturation, value/brightness) of the oil that is shown through the camera (attached on the robot); this will ensure the user that the target for collection is secured according to their vision.

Design process

To design a semi-autonomous surface oil-collecting robot, it will consist of various categories; starting with the Floatation Mechanism, it make uses of two pontoons to ensure the robot, with or without the collected oil, will be able to keep afloat wherein buoyancy was calculated; Collection Mechanism make use of a pressurized vacuum to be able to capture the wanted oil, this includes the coconut husk filters that is utilized to separate the oil and water; Components such as the Oil Container, Servo Motors, and DC Motors for the robot to function; Oil Detection proponents made use of HSV and Haar Cascade to be able to identify where oil is located given a body of water; for Programming, Arduino was used to ensure the robot’s mobility while Python was utilized for the overall code; finally, the User Interface was created in PyQT5, ensures the user and the robot are coordinated. The user will be able to control the image processing detected by the camera, as well as the manual Arduino movements.

How it is different

Our robot makes use of image processing, as a way to guide it to its target location, i.e. the oil spill, automating the collection process. It can also be controlled remotely if necessary. Additionally, it makes use of coconut husk as a way to filter the oil into a storage unit. Its exterior casing and floatation system is made of 3D printed technology for a lighter, cheaper design that is easy to assemble.

Future plans

Our plans were to further improve our design by testing the "ongoing" prototype on open waters; explore other sorts of filtration techniques and/or computer vision image processing techniques which is efficient for this design; and possibly add/change additional components such as a Ladar sensor, wireless connection, etc. that will be the most cost-effective and reliable for users to purchase. Once we were able to finalize our design, we wanted to offer it to oil companies and government organizations by reducing their administrative clean-up expenses; for non-profit organizations, the device will help towards mitigating environmental damage.

Awards

||CHAMPION - Philippine Association of Engineering Schools (PAES) Undergraduate Engineering Design Contest || Young Investigator Award - 5th Philippine Solid & Hazardous Waste Management Conference|| Semi-Finalist - InnovateFPGA Design Contest ||Excellence Award - 17th Digital Signal Processing Creative Design Contest ||