What’s The Good And Bad About Robotic Shark

Tracking Sharks With Robots

Scientists have been tracking sharks using robots for years. But a new design allows them to do this while tracking the animal. Biologists from Mote Marine Laboratory and engineers at Harvey Mudd College developed the system using components from the shelf.

It has a powerful gripping force, able to withstand pull-off forces that are 340 times its own weight. It can also sense and alter its path based on changing objects in the home.

Autonomous Underwater Vehicles

Autonomous underwater vehicles (AUVs) are robots that are programmable and according to their design they can drift, drive or glide across the ocean with no real-time supervision from human operators. They come with a range of sensors that record water parameters, robotvacuummops and to explore and map ocean geological features, seafloor habitats and communities, and more.

They are controlled by a surface ship using Wi-Fi or acoustic links to transmit data back to the operator. The AUVS is able to collect spatial or temporal data, and are able to be used as a group to cover more ground faster than one vehicle.

Similar to their land counterparts, AUVs can navigate using GPS and the Global Navigation Satellite System (GNSS) to determine where they are in the world and how far they’ve traveled from their beginning point. This information about their location, along with sensors for the environment that transmit information to the computer systems onboard, allows AUVs to travel on a planned course without losing sight of their destination.

After completing a research mission after completing a research project, the AUV will be able to float back to the surface. It will then be recovered by the research vessel from the vessel from which it was launched. Or an AUV that is resident can be submerged and conduct regular pre-programmed inspections for a period of months. In either case, an AUV will periodically surface to transmit its location via a GPS or acoustic signal, which is then transmitted to the vessel that is on the surface.

Some AUVs can communicate with their operators on a continuous basis via a satellite connection on the research vessel. This allows scientists to continue to conduct experiments from their ship even when the AUV is away collecting data underwater. Other AUVs communicate with their operators at specific times. For example when they require to refill their sensors or verify their status.

Free Think claims that AUVs are not only used to collect oceanographic data but also for the search of underwater resources, including gas and minerals. They can also be employed to respond to environmental catastrophes like tsunamis or oil spills. They can also be used to monitor subsurface volcanic activity and monitor the conditions of marine life, such as coral reefs and whale populations.

Curious Robots

Unlike traditional undersea robots, which are preprogrammed to search for a single element of the ocean floor, curious robots are designed to explore the surroundings and adapt to changing conditions. This is important, because the underwater environment is often unpredictable. For example, if the temperature of the water suddenly increases it could alter the behavior of marine animals or even cause an oil spill. The robots are designed to swiftly and effectively detect changes in the environment.

Researchers are developing a new robotic platform which uses reinforcement learning to teach robots to be curious. The robot, which appears like a child with yellow clothing and a green arm, can be taught to spot patterns that could indicate an interesting discovery. It can also be taught to make decisions based on the past actions. The findings of this research could be applied to create an artificial intelligence that is capable of learning on its own and adapting to changes in its environment.

Other scientists are using robots that are curious to investigate areas of the ocean that are too risky for human divers. Woods Hole Oceanographic Institution’s (WHOI) for instance, has a robot called WARP-AUV which is used to investigate shipwrecks and find them. This robot is able to detect reef creatures and distinguish jellyfish and semi-transparent fish from their dim backgrounds.

This is an impressive feat considering that it takes a long time to train a human to do this job. The brain of the WARPAUV has been trained by feeding it thousands of images of marine life making it able to recognize familiar species upon its first dive. The WARP-AUV is a marine forensics device that also sends real-time images of sea creatures and underwater scenery to supervisors on the surface.

Other teams are working on robots that can learn by observing the same curiosity humans do. A team at the University of Washington’s Paul G. Allen school of Computer Science & Engineering, for instance, is examining ways to help robots develop curiosity about their surroundings. This group is part of a three-year project by Honda Research Institute USA to develop curious-minded machines.

Remote Missions

There are many uncertainties in space missions that could lead to mission failure. Scientists don’t know how long a mission can last, how well the spacecraft parts will function and if other forces or objects might affect the operation of the spacecraft. The Remote Agent software is designed to help reduce the uncertainty. It will be able to perform a variety of the complicated tasks that ground personnel would do if they were on DS1 at the time of the mission.

The Remote Agent software system includes a planner/scheduler, an executive model-based reasoning algorithm. The planner/scheduler produces a set of activities based on time and events, known as tokens, which are then sent to the executive. The executive decides on how to make these tokens an array of commands that are directly transmitted to the spacecraft.

During the test, a DS1 crew member is present to assist in resolving any problems that may arise outside of the scope of the test. Regional bureaus must adhere to Department guidelines for managing records and keep all documentation related to the establishment of a remote mission.

SharkCam by REUS

Researchers have no idea of the activities of sharks beneath the surface. Scientists are breaking through the blue haze by using an autonomous underwater vehicle known as REMUS SharkCam. The results are both incredible and terrifying.

The SharkCam team is a group of Woods Hole Oceanographic Institution, took the torpedo-shaped SharkCam to Guadalupe Island last year to observe and film great white sharks in their natural habitat. The 13 hours of video footage combined with the visuals from the acoustic tag that is attached to the sharks reveal much about their behavior underwater.

The REMUS SharkCam, which is built in Pocasset, MA by Hydroid, is designed to follow the location of a animal that is tagged without disrupting its behavior or causing alarm. It utilizes an multidirectional ultra-short baseline navigation device to determine the range, bearing and depth of the Efficient Shark AI Robot Vacuum: XL Self-Emptying Pet-Friendly, then closes in at a predetermined standoff distance and location (left, right, above or below) to film it swimming and interacting with its environment. It can communicate with scientists at the surface every 20 second and accept commands to change relative speed, depth or standoff distance.

When Roger Stokey, REMUS SharkCam creator Roger Stokey, and Edgar Mauricio Hoyos Padilla, Pelagios Kakunja shark researcher from Mexico’s Marine Conservation Society, first imagined tracking great whites using the self-propelled REMUS SharkCam torpedo, they were concerned that the torpedo could interfere with the sharks’ movements and possibly make them fearful of. However, in a recent article published in the Journal of Fish Biology, Skomal and his colleagues write that despite nine bumps and bites from great whites weighing thousands of pounds in the course of a week of research off the coast of Guadalupe, the SharkCam was able to survive and revealed some fascinating new behaviors about the great white shark.

The researchers interpreted the sharks’ interactions with REMUS SharkCam, which had been monitoring and recording the activities of four sharks tagged as predatory behavior. They documented 30 shark interactions with the robot, including bumps, simple approaches, and on nine occasions, aggressive bites from sharks that appeared to be aiming at REMUS.