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RSE Unveils Lionfish Guardian LF1, Mark 4 Robot with Visual Recognition System for AI Aided Precision Fishing at Amazon re:MARS

The RSE Guardian LF1, Mark 4 ROV delivers depth, ease-of-use, under $1000 enabling fishermen and eco-tourists to reduce lionfish devastation

Founded by roboticists, environmentalists and scientists, Robots in Service of the Environment (RSE) is a 501(c)(3) non-profit organization focused on developing robot technology to solve environmental problems.

News provided by

RSE: Robots in Service of the Environment

Jun 04, 2019, 08:30 ET

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LAS VEGAS, June 4, 2019 /PRNewswire/ -- RSE: Robots in Service of the Environment, a non-profit organization developing robotic technology to solve environmental problems, today announced the Guardian LF1, Mark 4 undersea robot with a Visual Recognition System to aid fishermen and tourists in the tracking and capture of lionfish in the Atlantic. Going deeper than ever before, the Guardian LF1, Mark 4 is the first Guardian prototype to deliver advancements in AI aided precision fishing.

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RSE Unveils Lionfish Guardian LF1, Mark 4 Robot with Visual Recognition System for AI Aided Precision Fishing
RSE Unveils Lionfish Guardian LF1, Mark 4 Robot with Visual Recognition System for AI Aided Precision Fishing
The RSE Guardian LF1, Mark 4 is the first of its kind to introduce a Visual Recognition System of software and sensors which assists operators (fisherman and tourists) in navigation, maneuvering, tracking and capturing lionfish especially in rough seas.
The RSE Guardian LF1, Mark 4 is the first of its kind to introduce a Visual Recognition System of software and sensors which assists operators (fisherman and tourists) in navigation, maneuvering, tracking and capturing lionfish especially in rough seas.

The platform has successfully achieved original business goals of reaching depths up to 1000 feet and hitting a target cost price of less than $1000 USD, moving RSE even closer to a commercially available lionfish hunting robot.

With the suite of component systems featured in the Guardian LF1, Mark 4 remotely operated vehicle (ROV), the platform is specifically designed for rapid and easy lionfish capture while also creating a vast fleet of robots at a low cost.

Intended for use by fishermen, tourists and environmentalists, affordability and ease-of-use are essential to creating economic incentives for Guardian LF1 operators to reduce the lionfish population.

"In order to truly impact the lionfish population there will need to be thousands of robots in the water capturing the fish wherever they are. The affordable and easy to use Guardian LF1 will enable fishermen to profit, feeding the demand for lionfish while also reducing the devastating environmental impact of this invasive species," said Erika Angle, RSE co-founder and Director of Education. "With AI aided precision fishing, the Guardian LF1 is an effective and easy to use solution to reduce the population of these indiscriminate and voracious predators invading the western Atlantic."

RSE Guardian LF1, Mark 4 has been designed with a target of capturing 200 lionfish a day. The average weight of a single lionfish is 1.25 lbs. and can be sold for upwards of $7.99 a pound. On a successful day, an operator of an LF1 robot could earn around $1,500 to $2,000 a day on the sale of lionfish.

AI Aided Precision Fishing with Visual Recognition Software
The Guardian LF1, Mark 4 is the first of its kind to introduce a Visual Recognition System of software and sensors which assists operators (fishermen and tourists) in navigation, maneuvering, tracking and capturing lionfish especially in rough seas. The RSE team continues optimization of the software with cutting edge machine learning algorithms -- training the algorithms with current ROV capture footage and will soon improve upon the accuracy with crowdsourced footage from operators in the future.

In addition to the revolutionary visual recognition software, an Optical Flow Visual Algorithm has been developed on the ROV. This Optical Flow Visual continues to improve through software optimization, closing in on near-perfect obstacle avoidance and automated ROV stability in rough waters for future autonomy.

Even Deeper Than Before
Operational improvements to the Guardian LF1, Mark 4, include a main electronics enclosure rated for 1150 feet. This allows the ROV to reach depths of 1000 ft, far below where sport divers can access. Equipped with both a battery and power over tether system, the Mark 4 is able to be continually deployed underwater, significantly increasing the amount of lionfish an operator can capture in a day.

RSE at re:MARS (June 4 – 7, 2019 in Las Vegas, NV) 
Erika Ebbel Angle, a RSE co-founder will be a speaker at re:MARS, Amazon's AI and robotics event taking place from June 4 – 7, 2019 in Las Vegas, NV. At a Leadership Session on Wednesday, Erika will discuss the importance of leveraging robotic technology to reducing the devastating impact of this invasive species. The Guardian LF1, Mark 4 will be on display at re:MARS in the Tech Showcase where RSE will demonstrate AI aided precision fishing.

About RSE: Robots in Service of the Environment
Founded by roboticists, environmentalists and scientists, Robots in Service of the Environment (RSE) is a 501(c)(3) non-profit organization focused on developing robot technology to solve environmental problems. Established in the fall of 2015, the non-profit's first project is to develop an undersea robot to slow the destruction caused by the lionfish, an invasive species that is drastically reducing biodiversity and coral reef health in all warm waters of the western Atlantic. By combining technology development with mass manufacturing techniques, RSE offers a unique set of capabilities to solve some of the world's most challenging environmental problems on a massive scale.

RSE Social Media
For more information about RSE and our ongoing mission to solving large-scale environmental challenges, please visit www.robotsise.org; on Twitter @robotsise and Facebook.

SOURCE RSE: Robots in Service of the Environment

Related Links

http://www.robotsise.org

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